Remote Jobs Across Engineering, Product, and Data

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31 Companies

Mid-Level Data Engineer / Analyst

Cogniify

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other protected characteristic.

Data Engineer3 hours ago

Full Time Remote Mid Level

Role Description We’re seeking a Mid-Level Data Engineer/Analyst to independently design, build, and optimize data pipelines and analytics solutions that power business intelligence and AI/ML initiatives. In this role, you will own key data workstreams end to end, build production-grade transformation layers using dbt and Spark, manage data infrastructure on Snowflake and Databricks, and collaborate with analysts, data scientists, and product teams to deliver reliable, well-governed, and high-quality data products. You will also contribute to the maturity of our DataOps and data observability practices. - Design, build, and maintain production-grade ETL/ELT pipelines using dbt, Apache Spark (PySpark), Airflow, Dagster, or Prefect. - Develop and optimize data models on Snowflake, Databricks, BigQuery, or Redshift following dimensional modeling, data vault, or One Big Table patterns. - Implement and manage data ingestion from diverse sources including databases, REST/GraphQL APIs, event streams (Kafka, Kinesis), SaaS platforms, and flat files using Fivetran, Airbyte, or custom connectors. - Build and maintain semantic/metrics layers and curated data products for analytics, reporting, and self-service consumption. - Implement data quality, testing, and observability frameworks using dbt tests, Great Expectations, Soda, Monte Carlo, or Datafold. - Create advanced dashboards, reports, and analytical visualizations using Tableau, Looker, Power BI, or Sigma Computing. - Optimize query performance, pipeline efficiency, and cloud data platform costs across Snowflake, Databricks, or BigQuery. - Collaborate with data scientists and ML engineers to prepare and serve feature datasets for machine learning models. - Implement DataOps practices including CI/CD for data pipelines, version-controlled transformations, and automated testing. - Write production-quality Python and SQL code with proper testing, documentation, and error handling. - Support data governance initiatives including cataloging, lineage tracking, access controls, and PII management using tools like Alation, Atlan, DataHub, or Unity Catalog. Qualifications - Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. - 3–5 years of professional experience in data engineering, analytics engineering, or a closely related role with production delivery. - Strong proficiency in SQL and experience writing complex transformations, window functions, CTEs, and performance-tuned queries. - Hands-on experience with at least one modern data platform: Snowflake (strongly preferred), Databricks, BigQuery, or Redshift. - Experience with dbt (data build tool) for data transformation, testing, and documentation in production environments. - Working knowledge of Python (Pandas, PySpark, or Polars) for data processing and pipeline development. - Experience with workflow orchestration tools: Airflow, Dagster, Prefect, or cloud-native equivalents (AWS Step Functions, Azure Data Factory). - Familiarity with data ingestion tools and patterns: Fivetran, Airbyte, CDC (Debezium), or streaming ingestion (Kafka, Kinesis). - Experience with data visualization and BI tools: Tableau, Looker, Power BI, or Sigma. - Understanding of data modeling methodologies (Kimball, Data Vault, OBT) and data warehousing best practices. - Familiarity with version control (Git), CI/CD for data, and Agile development workflows. Preferred Qualifications - Snowflake SnowPro Core, Databricks Data Engineer Associate, or AWS Data Analytics Specialty certification. - Experience with Apache Spark and Databricks for large-scale data processing and lakehouse architectures. - Familiarity with data cataloging and governance tools: Alation, Atlan, DataHub, Collibra, or Databricks Unity Catalog. - Experience with data observability platforms: Monte Carlo, Datafold, Soda, or Elementary. - Exposure to streaming data pipelines using Kafka, Spark Structured Streaming, Flink, or Kinesis. - Experience with metrics/semantic layers: dbt Semantic Layer, Cube, or Looker Modeling Language (LookML). - Knowledge of cloud data infrastructure: AWS (S3, Glue, Athena, Redshift, Lake Formation), Azure (ADLS, Synapse, Data Factory), or GCP (GCS, Dataflow, BigQuery). Benefits - Unlimited PTO. - Very generous parental leave, much above industry standards. - Entrepreneurial culture where pushing limits and taking risks is everyday business. - Open communication with management and company leadership. - Small, dynamic teams = massive impact. - Medical, Dental and Vision coverage for employees. - Access to Disability & Life insurance. - Mental health and wellbeing support. - Annual bonus program. - Employer Stock Purchase Program (ESPP). - Yearly Team building experiences. - Mentorship and sponsorship opportunities. - Manager resources and support.

View details: Mid-Level Data Engineer / Analyst

United States

$91.9K - $144.1K / year

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Data Engineer

payabl.

We're powering the growth of merchants by helping them take payments easily, securely and globally.

Data Engineer2 days ago

Full Time Remote Mid LevelTeam 51-200H1B No Sponsor

Company Site LinkedIn

Role Description The role is about: - Data Team, where you play a vital role in collecting, analyzing, and interpreting data to support decision-making across the organization. - Your tasks include data collection, ensuring quality, and developing databases. - You're skilled in SQL, Python for data manipulation and visualization tools. - Collaborative and communicative, you work with various teams to understand their needs and provide actionable insights. - Passionate about staying updated with new technologies, you drive innovation and contribute to a culture of continuous improvement. Location: remote Poland, Portugal or on-site Cyprus Reporting to: Head of Engineering What you will do: - Lakehouse Architecture and Data Platform Design - Design, build, and maintain scalable data lakehouse solutions on AWS using S3, Apache Iceberg, and AWS Glue Catalog as core platform components. - Contribute to the evolution of the medallion architecture, ensuring that bronze, silver, and gold layers are reliable, performant, and aligned with business needs. - CDC and Streaming Data Ingestion - Build and support real-time and near-real-time ingestion pipelines that stream operational data from on-premise databases into AWS using Debezium, Kafka, Kafka Connect, and Iceberg sinks. - Monitor and troubleshoot streaming pipelines, including connector issues, schema changes, data consistency, and ingestion reliability. - Data Modelling and Business-Ready Layers - Design and implement silver and gold layer datasets that transform raw operational data into trusted, business-ready data products. - Work closely with analysts, analytics engineers, and business stakeholders to understand requirements and create reusable, well-structured data models. - Batch and Distributed Processing - Develop and maintain batch and distributed processing jobs using PySpark on AWS EMR and AWS Glue. - Optimize data transformation jobs for performance, scalability, reliability, and cost efficiency. - Data Integration and Orchestration - Build and maintain data workflows using Apache Airflow for API ingestion, batch processing, and orchestration across the medallion architecture. - Support integrations from external and third-party systems using tools such as Airbyte. - Data Quality, Governance, and Reliability - Implement data quality checks, validation processes, and reconciliation logic to ensure trusted and consistent datasets across the platform. - Contribute to data governance practices around documentation, ownership, lineage, access, and compliance. - Infrastructure and DevOps Collaboration - Collaborate on AWS infrastructure and deployment practices, working with services such as S3, Glue, EMR, IAM, EKS, and related platform components. - Support infrastructure-as-code workflows using Terraform and Terragrunt in collaboration with engineering and infrastructure teams. Qualifications - Minimum 3+ years of experience in data engineering or related roles. - Strong experience with SQL and data modeling for analytics and reporting use cases. - Strong programming experience with Python, ideally including PySpark. - Experience designing and maintaining ETL/ELT pipelines in production environments. - Experience with real-time or near-real-time data ingestion. - Experience working with Kafka or similar streaming technologies. - Experience with CDC concepts and tools such as Debezium. - Experience with data lake or lakehouse architectures on cloud platforms. - Hands-on experience with AWS data services such as: S3, Glue Catalog, Glue Jobs, EMR, IAM, Related AWS services. - Experience with Apache Iceberg, Delta Lake, or similar open table formats. - Experience designing curated analytics layers, such as silver and gold layers in a medallion architecture. - Experience with orchestration tools such as Apache Airflow or Dagster. - Experience working with relational databases such as MySQL, MariaDB, or PostgreSQL. - Working knowledge of Unix/Linux environments and shell scripting. - Understanding of data quality, governance, lineage, and production monitoring concepts. Good to Have - Experience with Apache Druid, ClickHouse, Snowflake, Databricks, or other analytical databases and warehouse platforms. - Experience with Airbyte or similar data integration tools. - Experience with dbt or collaboration with analytics engineering teams. - Experience with Terraform and Terragrunt. - Experience with Docker and Kubernetes. - Experience optimizing Spark jobs on EMR or AWS Glue. - Experience with data visualization tools such as: Tableau, Power BI, Superset, AWS QuickSight. - Experience with data observability, alerting, and monitoring tools. Benefits - Future-Proof Your Finances: Once you’ve passed probation, we’ll kickstart your Provident Fund to secure your future. - Grow with Us: Annual Learning Budget for professional development (eligible after probation)—because your growth is our growth. - Wolt Your Way Through Lunch: €150 monthly Wolt allowance to keep you fueled and happy. - Stay Active Your Way: Enjoy a SportsBenefits membership giving you access to a wide variety of gyms and sports facilities to support your active lifestyle. - Drive in Style: After one year with us, you may be eligible for a company car—performance and availability permitting. - Park with Ease: Complimentary parking space just steps from the office, so your commute is as smooth as your workday. - Max Out Your Downtime: 25 days of vacation + public holidays, plus an additional 10 sick days. - Shop & Save: Exclusive local discount card + tickets for exciting events like Beonix, basketball games, and more. - Speak Like a Local: Join free Greek language classes, twice a week, open to all team members. - Celebrate Together: We bring colleagues from all offices together for unforgettable company celebrations. - Global Collaboration & Events: Opportunities to participate in international company events and initiatives, connecting with colleagues from all regions and contributing to a truly global community. Hiring Process - Step 1 – Thinking in Action (45 minutes): Your first conversation will be with our Talent Acquisition team. We'll explore your background, career journey, motivations, and overall fit for the role. As part of this discussion, you'll also complete a short technical screening that will be reviewed by our engineering team. - Step 2 – Build in Production (60–90 minutes): Meet with the Hiring manager and technical experts for a practical assessment. Depending on the role, this may involve a live coding exercise or a real-world scenario designed to evaluate your technical skills, problem-solving approach, and ability to work through challenges similar to those faced by our teams. - Step 3 – Final Interview (45 minutes): The final stage is a group interview with senior members of our Technology squad, which may include the CTO and Head of Engineering. Together, we'll discuss team fit, collaboration style, expectations from both sides, and any remaining questions about the role, team, or technology domain. Let's embark on a journey to redefine the landscape of payments together. We're not just offering a role; we're inviting you to be a part of something bigger. Join our team, and let's innovate, disrupt, and lead the future of payments. Together, we can make an impact that resonates. Welcome to the team! Please review our Privacy Policy to understand how we process your personal data during the recruitment process: https://payabl.com/privacy-policy

View details: Data Engineer

Portugal + 2 more

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Azure Cosmos DB Architect / Senior Engineer

Nexaminds

Cloud Engineer11 days ago

Full Time Remote Senior

Role Description We are seeking an experienced engineer with deep expertise in Azure Cosmos DB to help design, optimize, and modernize enterprise applications. This role is heavily focused on Cosmos DB architecture, data modeling, migrations, and performance optimization rather than traditional data engineering. - Design and implement scalable solutions using Azure Cosmos DB. - Lead migrations from Microsoft SQL Server to Azure Cosmos DB. - Design document models, partition key strategies, indexing policies, and schema evolution. - Optimize Cosmos DB performance, scalability, throughput (RU/s), and cost. - Implement Change Data Capture (CDC) solutions using Debezium. - Design and support event-driven architectures, including event schema design and versioning. - Collaborate with engineering teams to build reliable, cloud-native applications. Qualifications - Deep hands-on experience with Azure Cosmos DB. - Strong experience with Microsoft SQL Server. - Experience migrating relational databases to Cosmos DB. - Expertise in document database design, partitioning strategies, indexing policies, performance tuning, RU optimization, and consistency models. - Experience with CDC and Debezium. - Strong knowledge of Event-Driven Architecture and event schema design. Requirements - Nice to have: HCM, payroll, benefits, or tax domain experience. - Familiarity with Azure Service Bus, Azure Container Apps, or Terraform. - Background working in a formal modernization or re-platforming program. Benefits - Stock options 📈 - Remote work options 🏠 - Flexible working hours 🕜 - Benefits above the law - Access to mentorship and tons of opportunities to learn and level up.

Azure Performance Optimization Data Engineering Microsoft SQL Server Debezium Terraform

View details: Azure Cosmos DB Architect / Senior Engineer

Mexico

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Data Platform Architect

Nexaminds

Architect13 days ago

Full Time Remote Mid Level

Role Description Nexaminds is looking for a Data Platform Architect to join a large-scale platform modernization program focused on decomposing a complex enterprise monolith into modern, distributed services. The ideal candidate has hands-on experience modernizing enterprise applications, migrating data from Microsoft SQL Server to Azure Cosmos DB, designing event-driven architectures, and defining scalable data models for distributed systems. - Lead the definition of data ownership, SQL-to-NoSQL migration strategies, event schema standards, and cross-domain data architecture. - Partner closely with architects and engineering teams to enable a seamless transition from a legacy monolithic platform to a cloud-native, microservices-based architecture. Qualifications - Data architecture experience, including work on large-scale legacy systems with significant relational complexity. - Hands-on experience untangling shared or cross-domain data models. - Direct experience migrating from relational (Microsoft SQL Server) to document (Azure Cosmos DB) data models at production scale. - Strong event-driven architecture experience, including event schema design, schema versioning, consumer contracts, and evolution strategy at scale. - Solid understanding of CDC (Change Data Capture) patterns and tooling (Debezium or equivalent). - Ability to set architecture standards that distributed teams implement independently. - Fluency working with application architects and engineers. - Familiarity with Azure Service Bus, Azure Container Apps, or Terraform. Requirements - Nice to have: HCM, payroll, benefits, or tax domain experience. - Background working in a formal modernization or re-platforming program. Job Duties - Analyze the monolith database to identify domain boundaries, shared data, and extraction sequencing. - Define SQL Server → Cosmos DB migration patterns and standards. - Design the data ownership and access model for cross-domain entities. - Define canonical event schemas for domain extraction and own the evolution and governance strategy. - Maintain reporting continuity throughout extraction. - Partner with the data lake architect to align on CDC output contracts and event schema standards. - Identify data-level risks in the extraction sequence early. - Contribute to decomposition planning sessions with data-grounded input. Benefits - Stock options 📈 - Remote work options 🏠 - Flexible working hours 🕜 - Benefits above the law - Access to mentorship and opportunities to learn and level up.

Microsoft SQL Server Azure Distributed Systems NoSQL Microservices Debezium Terraform

View details: Data Platform Architect

Mexico

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Lead Data Engineer

FYST

Data Engineer15 days ago

Full Time Remote LeadTeam 51-200

Role Description Your Mission - Design the target-state data architecture: Postgres CDC → Kafka → Snowflake → client-facing data products. - Own tooling decisions across ingestion, orchestration, transformation, and quality layers. - Implement CDC-based ingestion from PostgreSQL services (RDS, Aurora, EC2, K8s operator) using Debezium or equivalent. - Build streaming and near-real-time pipelines with defined SLAs. - Build a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting. - Define quality checkpoints across the full pipeline — from source capture through Snowflake to client delivery. - Define and enforce data contracts with service-owning teams for core entities: transaction, merchant, settlement, and processing status. - Build the external data delivery layer: financial settlement, transaction status, processor reconciliation, and client analytics. - Design tenant separation and implement replay/reload mechanisms for failure recovery. - Start hands-on, then gradually hire and grow a small data engineering team as the function matures. - Build a pragmatic roadmap with concrete deliverables at 3, 6, and 12 months. Qualifications - 5+ years in data engineering with end-to-end ownership of production pipelines. - Hands-on with Snowflake, PostgreSQL CDC (Debezium preferred), and Kafka. - Solid AWS experience — S3, RDS, Aurora, and cloud data infrastructure. - Data quality engineering mindset: monitoring, reconciliation, lineage. - Comfortable defining data contracts and driving requirements with backend engineering teams. - Technical leadership experience: project ownership, cross-team alignment, delivery under constraints. - Kubernetes, Airflow/Prefect/Dagster, and dbt are strong pluses. - Payments domain knowledge — settlement, transaction lifecycle, processor integrations — is a strong plus. - Familiarity with gRPC, RabbitMQ, and reading Go/Python service code is expected. - English language skills at the B2 level and fluent Russian language. Benefits - An opportunity to make something great even greater, you can be the reason why we grow, develop, and become the best fintech company on the market! - Career prospects - we are young, we have huge ambitions, and it is important that our employees grow with us. - Work with coworkers who are passionate about their business. - Compensation that will fully correspond to the competence and knowledge, with yearly performance reviews. - Remote work. - 20 days of vacation time; bank holidays; sick leaves; additional birthday day off.

PostgreSQL Apache Kafka Snowflake Amazon RDS Amazon EC2 Kubernetes Debezium Data Engineering AWS Amazon S3 Observability/Monitoring Airflow dbt Payments gRPC RabbitMQ Python

View details: Lead Data Engineer

Poland

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Senior MySQL Engineer

Insight Global

Founded in 2001, Insight Global (IG) offers enhanced staffing, placement staffing, and temporary-to-permanent staffing services, including long-term and short-t

Backend Engineer18 days ago

Full Time Remote Senior

Company Site

Title: REMOTE Senior MySQL Engineer Location: Remote (North America/Canada)Remote Job Type: Full-time (Permanent) Work Arrangement: 100% Remote Salary: $170,000–$190,000 USD per year (estimated) Job Description: An entertainment client is seeking a Database Engineer (MySQL) to join their team! This role focuses on supporting and improving large-scale MySQL environments across hundreds of nodes, including ongoing migration work and daily production support. Engineers split time between project-based work (rebuilding environments, improving tooling, automation) and BAU tickets (troubleshooting issues, schema updates, performance tuning), while participating in a follow-the-sun on-call rotation supporting high-traffic events. The team is highly focused on automation, documentation, and proactively solving issues before they become incidents. You’ll be working in a Linux-heavy, hands-on environment where engineers are expected to deeply understand and operate the systems they support. This is a full-time, remote position based in North America/Canada with a rotating on-call schedule. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Required Skills & Experience • 7+ years of hands-on MySQL engineering (strong in troubleshooting, optimization—not just DBA) • Strong Linux experience (daily terminal use, OS-level troubleshooting) • Expertise in query optimization, performance tuning, and replication • Experience supporting large-scale, high-availability production environments • Scripting experience (Bash and/or Python) • Experience with automation tools (Ansible, Terraform, or similar) • Ability to troubleshoot across DB, OS, and infrastructure layers • Foundational networking knowledge (ports, VPCs, access layers) • AWS experience (Aurora, RDS, EC2, etc.) • Strong automation mindset and interest in AI-driven efficiency Nice to Have Skills & Experience • Percona ecosystem (XtraDB Cluster, XtraBackup) • Kafka / Debezium / CDC pipelines • Monitoring tools (Prometheus, Grafana) • VMware or large-scale migration experience • Docker/Kubernetes or CI/CD pipelines • HashiCorp Vault or secrets management • Consulting/contracting background (multi-environment experience) • Exposure to LLM/AI tools for automation Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.

MySQL Linux Shell Python Ansible Terraform AWS Amazon RDS Amazon EC2 AI Apache Kafka Debezium Observability/Monitoring Prometheus Grafana VMware Docker Kubernetes CI/CD HashiCorp Vault LLM

View details: Senior MySQL Engineer

Canada + 1 more

$170K - $190K / year

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Fullstack Engineer (Semantic / Analytics)

Integrity Next GmbH

IntegrityNext, a global leader in supply chain sustainability software, stands at the forefront of corporate sustainability and compliance. Since 2016, businesses have trusted IntegrityNext to simplify ESG compliance, reduce risks, and address critical challenges like due diligence, decarbonization, and sustainability reporting. With over 500 customers and 2 million suppliers across 190 countries, IntegrityNext is transforming supply chains into engines of transparency and sustainable growth. We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We welcome applicants from all backgrounds and strive to create an environment where everyone feels respected and heard. Join us in our mission to build a more equitable and inclusive world.

Analytics Engineer19 days ago

Full Time Remote Mid Level

Role Description As a Fullstack Engineer (Semantic / Analytics) (m/f/d), you will own the business meaning of data and make it reusable across analytics, BI, APIs, semantic access, and AI-powered experiences. You will work across semantic modeling, KPI logic, reusable data models, business-facing data exposure, and collaborate closely with platform, AI, solution, and business teams. The platform will continue to evolve toward broader support for unstructured data and lakehouse-style capabilities. We work spec-driven, use AI-assisted engineering tools such as Claude Code and Cursor, follow “You build it, you run it”, and expect strong specialization combined with fullstack ownership. - Build the semantic foundation for data products - Build and evolve the semantic layer in dbt and Snowflake semantic views, including business entities, metrics, dimensions, and reusable data models - Define KPIs, business logic, canonical data definitions, and semantic consistency standards together with business and product stakeholders - Help shape how semantic data products are exposed consistently across internal and external platform capabilities - Ensure business entities, KPIs, and metrics are clearly and consistently defined across the platform - Make curated data usable across BI, APIs, and AI - Expose curated data for BI tools such as Amazon QuickSight and Apache Superset, APIs, downstream product use cases, and AI consumption including Snowflake Cortex AI - Support AI use cases through feature shaping, context structuring, semantic enrichment, and business-grounded data preparation - Collaborate with the AI Engineer to ensure agentic experiences are grounded in meaningful, well-structured business data - Help ensure BI, APIs, and AI use cases rely on the same trusted semantic foundations in Snowflake - Work with reliable, fresh, and governed data - Work with near-real-time data ingested from PostgreSQL into Snowflake via Snowflake Openflow - Ensure semantic models reflect fresh, reliable data from operational systems - Align with solution teams on data contracts, source semantics, and integration expectations - Help define validation rules, data trust practices, lineage support, and consistency controls - Collaborate across platform, product, and engineering - Work closely with the Data & Platform Architect and Data & Platform Engineer to build semantic models on reliable, scalable Snowflake foundations - Collaborate with platform, AI, solution, product, and business-facing teams - Help the company build a reusable semantic layer that scales with future platform growth - Apply spec-driven development, AI-assisted engineering workflows, and end-to-end production ownership Qualifications - Very strong hands-on SQL skills and broad, deep database knowledge, including data modeling - Strong hands-on experience with Snowflake, including Snowflake semantic views - Hands-on experience with dbt at scale for transformations and analytics engineering best practices - Experience with PostgreSQL as a source for structured business data - Experience building semantic layers, reusable metrics, canonical data models, analytics engineering assets, KPIs, business logic, and data definitions with stakeholders - Experience exposing data for BI, APIs, downstream product use cases, and AI or analytics consumption - Experience defining or supporting data contracts, validation rules, semantic consistency standards, data quality, lineage, and trust practices Requirements - Experience with near-real-time or CDC ingestion, ideally Snowflake Openflow or comparable tools such as Fivetran, Debezium, or Kafka - Strong Python skills - Experience building APIs and services such as REST or GraphQL - Experience exposing data and tools through interfaces such as MCP servers - Solid AWS stack know-how - Experience with BI tools such as Amazon QuickSight, Apache Superset, Looker, Tableau, Power BI, or similar platforms - Strong understanding of how data should be structured for AI, analytics, semantic access, and product consumption - Comfortable with structured, spec-driven delivery and AI-assisted development workflows Benefits - 30 days of paid vacation - EGYM Wellpass membership to support your work-life balance - Flexible working models to better balance work and personal life - Inspiring office spaces in the heart of Munich - Flexible remote work from home or anywhere within Germany - A professional, welcoming, and highly motivated team - Collaboration at eye level with an open feedback culture - An environment where people support each other and grow together - Short decision-making paths and real opportunities to shape things - Freedom to contribute and implement your own ideas - A high level of ownership and responsibility

AI dbt Snowflake Apache HTTP Server PostgreSQL SQL Debezium Apache Kafka Python GraphQL AWS Looker Tableau Power BI

View details: Fullstack Engineer (Semantic / Analytics)

Germany

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Principal/Staff Engineer (Data)

Arbor Education

Arbor MIS helps schools and MATs work more easily and collaboratively. Join a free webinar: http://bit.ly/Arbor-webinars

Full-stack Engineer26 days ago

Full Time Remote LeadTeam 51-200H1B No Sponsor

Company Site LinkedIn

Role Description As a Principal/Staff Engineer (Data) you will help drive architecture and technical strategy for our Data domain, spanning the entire journey from transactional source to analytical insight. You will evolve how data is leveraged across Arbor, delivering value that ensures our OLAP and AI capabilities provide a competitive edge and our OLTP foundations are built for scale. It’s a wide impacting and exciting role, crucial for Arbor's next stage of growth. We’re looking for candidates who are highly collaborative, energised by complex problems, and have a proactive approach. You will work collaboratively with multiple teams, Technical Leads, Product Directors, and Engineering Leadership to deliver strategic business objectives, all while reimagining ways of working to ensure we stay at the forefront of the industry’s AI evolution. Core Responsibilities - Define and evangelise target architectures that bridge our transactional, analytical, and AI systems, ensuring our data remains a competitive advantage. - Be a leader for our end-to-end data lifecycle, from OLTP schema design and migrations to OLAP governance, platform and analytics. - Partner with Technical Leads to provide hands-on guidance supporting feature delivery, tech debt paydown, and architecture improvements. - Collaborate with Product Directors to understand product vision and translate this into deliverables, aligning commercial and engineering goals. - Lead our shift to an AI-First way of working, architecting the data foundations to enable AI in our products and championing the latest approaches to help drive productivity gains. - Architect the future infrastructure required for LLM orchestration, Retrieval-Augmented Generation (RAG), and real-time model inference at scale. - Mentor and coach Technical Leads/Senior Engineers on architectural and engineering excellence, continually raising our bar and supporting career growth. - Act as a role model for technical leadership — work with pace, be pragmatic, and stay laser focused on outcomes not output. - Head up architectural reviews for your domain and ensure all designs meet Arbor’s quality, reliability, security and compliance standards. - Collaborate with Staff Engineers and Principal Engineers to shape Arbor’s broader technology strategy, working outside your domain as needed. - Partner with Engineering Management to help grow teams, identify and resolve systemic bottlenecks, ensuring the success of our strategic goals. Qualifications - Extensive experience overseeing data architecture and a track record of delivering iterative outcomes across one or more OLAP domains. - Strong understanding of data modelling techniques (Star, Medallion, etc) and distributed data systems within cloud-native environments (Snowflake, etc). - Experience in building and leveraging unstructured data across disparate systems to enable product development. - Examples of communication and influencing across technical and non-technical audiences to achieve positive outcomes. - An ability to support the growth of engineers and technical leads whilst still delivering value across distributed, cross-functional teams. - Demonstrable experience working in an ownership culture where quality, performance, observability, and security are core responsibilities for every engineer. - An understanding and opinion on how AI-first engineering will change the data ecosystem and ways of working, ideally with worked examples. - Examples of contributing to or leading technical communities of practice (e.g. chapters, guilds, architecture councils). - Practical knowledge of DataOps principles, including CI/CD for data and the orchestration of complex pipelines (e.g., AWS, Debezium, Git, Infra as Code). - Good commercial knowledge of data security standards, encryption at rest/transit, and relevant compliance laws. - Platform financial acumen - demonstrable experience of optimising SaaS platform spend, and the use of forecasting models. Bonus Skills - AI/ML Engineering & MLOps, including model deployment/serving and monitoring. - Experience with federated learning and/or privacy-enhancing technologies (PETs). - Direct experience with LLM Ops, including prompt engineering at scale, and token cost optimisation. Benefits - The chance to work alongside a team of hard-working, passionate people in a role where you’ll see the impact of your work everyday. - A dedicated wellbeing team who champion initiatives such as mindfulness, lunch n learns, manager training, mental health first aid training and much more! - 32 days holiday (plus Bank Holidays). This is made up of 25 days annual leave plus 7 extra company wide days given over Easter, Summer & Christmas. - Life Assurance paid out at 3x annual salary. - Comprehensive wellness benefit provided by AIG Smart Health, which provides a 24/7 virtual GP service, Mental health support, Counselling, and personalised Health Checks. - Private Dental Insurance with Bupa. - Salary sacrifice Pension provided by Scottish Widows. - Enhanced maternity and adoption leave (20 weeks full pay) and paternity (6 weeks full pay) pay. - 5 free return to work maternity coaching sessions, helping you adapt to this new exciting time of life! - Access to services such as Calm and Bippit (financial wellbeing coaching). - All of our roles champion flexible working and we are happy to discuss what this means to you. - Social committees that plan team, office and company wide events to bring people together and celebrate success. - Dedicated professional development training budget (CPD courses, upskilling resources, professional memberships etc). - Volunteer with a charity of your choice for a day each year. - Dog friendly offices! Interview Process - Phone screen - 1st stage - 2nd stage Company Description Arbor Education is an equal opportunities organisation. Our goal is for Arbor to be a workplace which represents, celebrates and supports people from all backgrounds, and which gives them the tools they need to thrive - whatever their ambitions may be so we support and promote diversity and equality, and actively encourage applications from people of all backgrounds.

AI AI Agents Snowflake Observability/Monitoring CI/CD AWS Debezium Git AI/ML LLMOps

View details: Principal/Staff Engineer (Data)

United Kingdom

£100K - £120K / year

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Senior Java Backend Developer

NearSource

NearSource is a global IT staffing and technology services firm helping enterprises build high-performance tech teams. We support innovation at scale by connecting skilled professionals to leading companies and impactful projects. We prioritize transparency, responsiveness, and the right fit. Equal Opportunity Statement NearSource welcomes applicants of all backgrounds, communities, and experiences. Our commitment to diversity, equity, and inclusion drives us to create hiring experiences that are open, fair, and human-first. Interested candidates can apply, and the recruitment team will review profiles based on alignment with client requirements.

Backend Engineer28 days ago

Contract Remote Senior

Role Description NearSource is seeking a Senior Java Backend Developer to contribute to a large-scale cloud-native platform for a Fortune 500 product company. This role requires strong expertise in backend engineering, event-driven architectures, distributed systems, and real-time data streaming. The successful candidate will be expected to quickly onboard and deliver value within the first weeks of engagement while collaborating with global engineering teams. - Design, develop, and maintain scalable backend services using Java or Go. - Architect and implement event-driven systems leveraging Apache Kafka and AWS streaming technologies. - Build and optimize high-throughput data processing pipelines and asynchronous messaging workflows. - Develop reliable distributed systems with strong focus on resiliency, scalability, and operational excellence. - Implement and maintain cloud-native solutions on AWS services including DynamoDB, MSK/Kinesis, ECS/EKS, IAM, and S3. - Design partitioning strategies, retention policies, access controls, and consumer architectures for Kafka-based platforms. - Drive implementation of data streaming solutions supporting CDC patterns and event processing requirements. - Apply distributed systems best practices including idempotency, retry mechanisms, eventual consistency, and fault tolerance. - Collaborate with cross-functional engineering teams to deliver production-ready software solutions. - Troubleshoot, optimize, and improve platform performance, scalability, and reliability. - Contribute effectively within an existing project environment and achieve rapid productivity during onboarding. Qualifications - 7 to 10 years of professional software engineering experience. - Strong backend development experience using Java with Spring Boot or Go with modern service frameworks. - Hands-on production experience with Apache Kafka, including: - Producer and consumer APIs - Partition design - Retention management - ACL configuration - Kafka Admin Client - Hands-on production experience with AWS services, including: - DynamoDB - MSK or Kinesis - ECS or EKS - IAM - S3 - Strong experience building event-driven architectures and streaming platforms. - Experience with Change Data Capture (CDC) patterns and asynchronous message processing. - Strong understanding of delivery guarantees, including exactly-once and at-least-once processing semantics. - Solid knowledge of distributed systems concepts including idempotency, retries with backoff, and eventual consistency. - Proven ability to join active projects and contribute effectively within the first one to two weeks. Requirements - Experience with Apache Flink, Flink SQL, or Kafka Streams. - Experience building stream consumers using AWS Kinesis Client Library (KCL). - Experience implementing Outbox patterns, Debezium, or similar CDC frameworks. - Experience with DynamoDB single-table design. - Familiarity with GitOps deployment methodologies using ArgoCD or Flux. - Familiarity with Apache Iceberg, Apache Paimon, or other open table formats. Benefits Apply now, or share your resume with salary expectations at careers@nearsource.ca. Thank you for considering a career with us! Once you submit your application, our Talent Acquisition team will review your resume thoroughly. If there's a strong match, we'll reach out to discuss your experience, role details, benefits, compensation, and next steps. While we strive for transparency, we may not be able to respond to every applicant due to high volume, but we genuinely appreciate your time and interest. Company Description NearSource Technologies is a trusted partner for future-ready software consulting, enabling Fortune 500 enterprises to accelerate digital transformation. Our global engineering teams build and deploy impactful technology for some of the world's most admired brands, working directly on long-term client initiatives. NearSource is an equal opportunity employer committed to fostering an inclusive and respectful environment. We celebrate diversity and do not discriminate based on race, gender, religion, sexual orientation, age, disability, or background. Innovation thrives when everyone feels empowered to contribute.

Java Distributed Systems Apache Kafka AWS DynamoDB Amazon Kinesis Amazon ECS Amazon EKS Amazon IAM Amazon S3 Spring Boot Apache Flink SQL Debezium Argo CD Flux Apache Iceberg

View details: Senior Java Backend Developer

Canada

C$80 - C$90 / hour

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Senior Data Platform Engineer

J.D. Power

J.D. Power is clear about what we do to ensure our success into the future. We unite industry leading data and insights with world-class technology to solve our clients’ toughest challenges. We POWER Our Customer's Success We are Innovative, Collaborative and Grounded in Data We Make Things Easy We Get It Done We Start with Trust & Prove it Everyday

Platform Engineer28 days ago

Full Time Remote SeniorTeam 1,001-5,000

Role Description Own the hands-on engineering of JD Power's Snowflake data platform. Responsible for translating the Platform Lead's architecture and governance direction into a production-grade, automated, and observable Snowflake environment that supports analytics, product, and AI/ML workloads across the enterprise. The Scope & Ownership You Will Have in This Role: - Owns Snowflake account, warehouse, and object architecture. - Infrastructure-as-Code repository and CI/CD for all Snowflake changes. - RBAC implementation, security controls, and identity integration. - Ingestion and integration patterns (Snowpipe, Streams/Tasks, managed connectors). - Platform observability, cost monitoring, and performance tuning. - Documentation, runbooks, and onboarding patterns for platform consumers. Does not own: - Governance policy and strategy (owned by the Platform Lead). - Business data modeling and semantic layer (owned by Analytics Engineering). - Source system data quality at point of capture (owned by upstream teams). What You’ll Be Doing in This Role: - Design and evolve Snowflake account, warehouse, and object architecture. - Implement and maintain all Snowflake objects, roles, and policies in Terraform. - Operate database CI/CD using Schemachange, Liquibase, or equivalent. - Tune performance: clustering, search optimization, materialized views, query profiling. - Build and maintain the functional/access role hierarchy enforcing least privilege. - Implement masking policies, row access policies, object tagging, and network policies. - Integrate Snowflake with IdP for SSO/SCIM; manage service accounts and key rotation. - Partner with InfoSec, Privacy, and Compliance on audit readiness and control attestation. - Operate Snowpipe, Snowpipe Streaming, Streams/Tasks, and Kafka Connector pipelines. - Manage Fivetran/Airbyte (or equivalent) connector deployments and reliability. - Implement Iceberg / external tables where lakehouse interoperability is required. - Integrate with orchestration (Airflow / dbt Cloud) and observability tooling. - Define and meet SLOs for platform reliability, freshness, and cost. - Build dashboards and alerting; lead incident response for platform issues. - Document architecture decisions, patterns, and runbooks. - Enable Analytics Engineering, Product Engineering, and Data Science consumers. Qualifications - 5+ years of professional data platform, data engineering, or data infrastructure experience. - 3+ years of hands-on Snowflake experience at production scale (not pilot/POC). - Demonstrated expertise in Snowflake RBAC design, warehouse sizing and cost governance, performance tuning, and security features. - Strong SQL — able to read and optimize a query profile. - Python for tooling, automation, and pipelines. - Production IaC experience — Terraform required; Snowflake provider strongly preferred. - Database CI/CD using Schemachange, Liquibase, dbt, or equivalent change-management tooling. - Cloud fluency in AWS — networking, IAM, storage, and Snowflake integration points. - Ingestion experience with Snowpipe, Streams/Tasks, Kafka, and/or Fivetran/Airbyte. - Communication — able to author decision records and runbooks; able to influence without authority. Requirements - SnowPro Advanced certification (Architect, Data Engineer, or Administrator). - Hands-on dbt and modern Analytics Engineering experience. - Experience with Snowflake Horizon Catalog, Polaris, Collibra, or Alation. - Streaming and CDC: Kafka, Debezium, Snowpipe Streaming, Dynamic Tables. - Iceberg / lakehouse architecture. - Data observability tooling (Monte Carlo, Bigeye, Datadog). - Automotive, financial services, insurance, or regulated consumer-data experience. - AI/ML workloads on Snowflake (Cortex, Snowpark, feature stores). Benefits - This position has a starting salary range of $120K -$150K USD/$110K -$120K CAD per year. - An employee’s pay within the range is determined by a number of factors, including relevant skills, education, qualifications, experience, performance, business or organizational needs, and geographic location.

View details: Senior Data Platform Engineer

United States + 1 more

$120K - $150K / year

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