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• Lead the systems, integrations, and operational infrastructure supporting business operations across the company. • Manage tier-1 IT support and resolve day-to-day issues with internal tools. • Design data flows and integrations across systems while leading projects and supporting AI tooling. • Collaborate with Operations, Finance, and Legal departments for efficiency. • Handle occasional off-hours responsibility for critical system outages. • Aim to establish a centralized internal knowledge base, audit internal platforms, enhance identity and access management, assess readiness for SOC 2, and create sustainable IT operational processes.
• Design, configure, and maintain AI agent workflows • Research and evaluate new approaches to agent orchestration • Guide and review AI-generated code with a critical eye • Build and maintain a RAW → Base → Data Marts pipeline • Own data pipelines end to end, from API ingestion through transformation and QA • Write and maintain tests and documentation at every layer of the pipeline • Build comprehensive test suites using Great Expectations or equivalent tooling • Implement business logic validation checks and automated quality monitoring • Implement complex business logic and data validation in Python • Build ETL scripts, automation workflows, and API integration scripts
Cortica, established in 2014, is a leading provider of advanced neurological therapies for children with autism and other developmental differences. The company
Role Description The Senior AI Data Engineer will serve as both architect and builder of our data ecosystem. Every initiative will follow a complete engineering lifecycle: - Gathering stakeholder requirements - Designing the solution - Building and testing it - Shipping it to production This role will work across data lakes, analytics pipelines, and lightweight application development— the multi-disciplinary data equivalent of a full-stack developer. The Senior AI Data Engineer will work closely with the data science, finance, and clinical operations teams to design intelligent, automated data solutions that power care decisions, financial planning, and operational efficiency. AI augmentation is not optional — it is the standard working mode. Qualifications - 5+ years of hands-on data engineering experience, including building and operating production data pipelines - Expert-level Python skills for ETL, pipeline orchestration, and automation - Deep SQL proficiency — query optimization, data modeling, stored procedures - 2+ years’ experience working with AI first development workflows - 4+ years’ experience with AWS (S3, Glue, Lambda, Redshift) and/or Azure big data services - 1+ year of experience with Snowflake - 2+ years of experience with orchestration frameworks - 2+ years of Salesforce experience with Apex and configurations - Experience with Kimball dimensional modeling — building star schemas and conformed dimensions in production - Power BI (or equivalent BI tool) experience — data model design and report development - API integration experience — REST, GraphQL, event streaming (Kafka, Kinesis, or similar) - Application development literacy — comfortable building lightweight web tooling (Python/Flask, Node, or similar) Requirements - Engage stakeholders directly to gather, clarify, and document project requirements - Translate requirements into architected data solutions - Own testing end-to-end — unit tests, data quality checks, reconciliation, and integration tests before anything reaches production - Deploy solutions to production and monitor post-deployment health - Run parallel AI coding sessions across different facets of a pipeline simultaneously - Build and maintain context files for data projects - Design verification loops: automated data quality checks, dbt tests, CI hooks, and pipeline monitors - Build MCP (Model Context Protocol) or equivalent integrations - Design and build complex, reliable data pipelines ingesting from various sources - Implement and evolve data models using Kimball methodology - Optimize pipeline performance, manage data quality, and perform root-cause analysis on data anomalies - Develop and maintain orchestration workflows in Python, and AWS Glue - Continuously evolve the data schema as business and engineering requirements change - Build and support Power BI data models and reports - Work with data analysts and data scientists to build reusable, well-documented pipeline components - Deliver data products that drive clinical care decisions, financial planning, and operational performance improvements - Build lightweight internal data applications and tooling - Design for agentic workflows - Integrate with Salesforce Health Cloud and other platforms using APIs and event-driven patterns - Ensure data security and HIPAA compliance in all pipeline and application work - Document decisions, tradeoffs, and architecture clearly - Collaborate across IT, finance, clinical operations, and data science Benefits - Medical, dental, and vision insurance - 401(k) plan with company matching and rapid vesting - Paid holidays and wellness days - Life insurance and disability insurance options - Tuition reimbursements for professional development and continuing education - Referral bonuses Company Description Cortica is a rapidly growing healthcare company pioneering the most effective treatment methods for children with neurodevelopmental differences. Our mission is to design and deliver life-changing care – one child, one family, one community at a time. Ultimately, we envision a world that cultivates the full potential of every child. At Cortica, every team member is instrumental in helping us achieve our mission! Our culture and values guide how we work and treat one another. Cortica celebrates diversity and fosters an inclusive environment, seeking ideas and opinions from everyone on the team.
The #1 Online Motivated Seller Lead Generation System For Real Estate Investors & Agents
Role Description Carrot is seeking a detail-oriented and analytically driven Global Payment Operations Specialist to join our growing team. In this role, you’ll help ensure the accuracy and efficiency of global payment processing while partnering closely with Customer Success and Member Success teams. You’ll also have opportunities to improve operational workflows, create or refine process documentation, and contribute to automation, scalability, and product enhancements that strengthen Carrot’s global payment experience for our members. Qualifications - Bachelor's degree in Economics, Finance, Business Administration or related field - 2+ years of professional experience in payment operations at a fintech or payments company or equivalent experience in banking - Strong understanding of payment processing workflows, including cross-border payments, currency conversions, and reconciliation - Experience working with payment platforms such as Stripe, Modern Treasury, Airwallex, and Corpay - High level of integrity, initiative, motivation and curiosity - Strong analytical skills, detail-oriented, and solid ability to communicate verbally and in writing - Strong knowledge of Microsoft Excel and/or Google Sheets - Comfort working and communicating with cross-functional teams and outside customers - Self-starter with the ability to effectively plan, coordinate, and deliver results with minimal guidance Requirements - Knowledge of payment and compliance standards, including Nacha, cross-border payments, IAT, PPD, CCD, and OFAC guidelines - Experience handling high-volume money movement or transactional payments under tight deadlines - Experience with NetSuite or similar ERPs - Process-oriented mindset with a focus on efficiency and automation; experience developing best practices and creating scalable systems - Passion for Carrot’s mission and enthusiasm for contributing to a collaborative, dynamic team environment Benefits - Holistic Total Rewards package designed to support employees in all aspects of their life inside and outside of work - Health and wellness benefits - Retirement savings plans - Short- and long-term incentives - Parental leave - Family-forming assistance - Competitive compensation package - Starting base salary for this position will range from $70,000-$80,000 Fraud and Security Notice Please note that all communication regarding job opportunities at Carrot will come exclusively from an @get-carrot.com email address. If you receive messages from any other domain, please disregard them and report the incident to: securityreporting@get-carrot.com Why Carrot? Carrot has received national and international recognition for its pioneering work, including: - Fast Company's Most Innovative Companies and World Changing Ideas - Inc. Power Partners - Modern Healthcare’s Innovators - Fortune’s Best Workplaces in Healthcare - Great Place to Work - Age-Friendly Employer certifications Carrot is regularly featured in media reporting on issues related to the future of work, women in leadership, and healthcare innovation.
Role Description The AI & Data Systems Engineer will be a key individual contributor on Ceribell’s Data Architecture & Engineering team, responsible for much of the hands-on implementation work that turns architectural plans into reality. This role exists at the intersection of software development, data engineering, and DevOps as someone who is equally comfortable writing application code and managing the infrastructure those systems run on. A significant part of this role involves taking ideas and early-stage prototypes for AI-powered internal tools and engineering them into stable, supportable internal applications. The ideal candidate is a versatile builder who can move fluidly across layers of the stack, understands when something is production-ready versus when it needs to be rebuilt properly, and takes pride in writing code and infrastructure that others can maintain and build on. What you'll do: - Implement internal tools and applications based on architectural direction from the Director of Data Architecture & Engineering, including taking stakeholder prototypes and re-engineering them into production-grade systems. - Manage and maintain the infrastructure supporting internal AI tools and data systems, including deployment, configuration, monitoring, and incident response. - Write clean, well-documented code across whatever languages and frameworks the work requires; apply sound engineering practices around testing, version control, and code review. - Evaluate and integrate AI tools and third-party services into internal workflows where they provide clear value, with attention to security, cost, and long-term maintainability. - Contribute to data quality practices: implementing automated checks, investigating pipeline failures, and helping establish clear data ownership and lineage. - Collaborate with stakeholders across the business to understand requirements, surface technical tradeoffs, and deliver solutions that meet actual needs rather than assumed ones. - Support access control and permissions management across systems and tooling, contributing to the team’s broader security and governance practices. - Maintain thorough documentation of systems, data flows, and processes so that institutional knowledge is preserved and accessible. - Other responsibilities as assigned by your Manager/Supervisor. Qualifications - 3 - 6 years of hands-on experience in a technical role spanning some combination of software development, data engineering, and infrastructure or DevOps work. - Experience implementing and deploying AI solutions in a production environment, including model integration, API usage, and operational maintenance. - Proficiency in at least one general-purpose programming language (e.g. Python) and comfort picking up new languages or frameworks as the work demands. - Experience building and maintaining data pipelines, including working with APIs, relational databases, and cloud data platforms. - Working knowledge of DevOps practices and tools: CI/CD pipelines, containerization (Docker), cloud infrastructure (AWS, GCP, or Azure), and infrastructure-as-code concepts. - Demonstrated ability to read and understand existing codebases, including prototypes or AI-generated code, assess their quality, and refactor or rebuild them as appropriate. - Familiarity with enterprise business systems such as Snowflake, Salesforce, NetSuite, or similar platforms, including working with their APIs and data models. - Strong attention to detail. - Good written and verbal communication skills; able to explain technical decisions clearly to non-technical colleagues. - Bachelor’s degree in Computer Science, Engineering, or a related field preferred; equivalent practical experience accepted. Requirements - San Francisco Bay Area, Los Angeles, and New York City Metropolitan Locations: $161K - $173K - All other National Locations: $141K - $162K - A candidate’s final salary offer will be based on their skills, education, work location and experience, and thus it may differ from the posted range. - Compensation may also include bonuses consistent with Ceribell’s corporate compensation plan. Benefits - Performance-based incentive compensation (varies by role) - Equity opportunities - 100% Employer paid Health Benefits for Employees - 50% - 70% Employer paid Health, Dental & Vision for dependents (depending on plan selection) - 100% paid Life and Long-Term Disability Insurance - 401(k) with a generous company match - Employee Stock Purchase Plan (ESPP) with a discount - Monthly cell phone stipend - Flexible paid time off - 13 Paid Holidays + 3 Company Wellness Days - Excellent parental leave policy - Fantastic culture with tremendous career advancement opportunities - Joining a mission-minded organization! Application Deadline Ongoing
Using CaaS (Codeless-as-a-Service) to accelerate time-to-market & eliminate legacy code for the enterprise 🚀
Role Description We're seeking an experienced Principal Data Engineer/Technical Lead who is passionate about implementation and capable of writing high-quality application code. In this role, your primary goal is to design and build the services, abstraction layers, and middleware that transform application data needs into specific, high-performance database operations and serve as a dynamic player-coach for our core data engineering squad. As a technical leader, you will directly impact system performance and latency issues that affect our enterprise customers while fostering an inclusive, high-performing engineering culture. Key Responsibilities - Act as a player-coach, providing technical direction, architectural guidance, and daily mentorship to a focused team of 3–5 engineers. - Conduct thoughtful code reviews and foster professional growth within your squad. - Design and implement sophisticated Data Access Layers (DAL) and custom ODMs to translate platform-generated, SQL-like queries into high-performance MongoDB BSON operations and aggregation pipelines. - Build and maintain middleware that ensures Unqork’s core business logic remains storage-agnostic, enabling seamless modularity and flexibility across different data storage mechanisms. - Architect and scale a multi-tenant, secure MongoDB ecosystem. - Lead strategies for ensuring high availability while performing deep-dive execution plan analysis (IXSCAN vs. COLLSCAN) to optimize query performance. - Plan and architect hybrid data architectures to support operational, transactional, and analytical schema and database systems. - Use Node.js and JavaScript to build robust microservices (typically GraphQL) and internal libraries that integrate dynamic, metadata-driven data patterns into the Unqork no-code runtime. - Design schemas and declarative models that allow non-technical users to build complex application logic without compromising data integrity or system performance. - Architect real-time and batch data pipelines using Apache Kafka and Spark to facilitate data transformation and movement between relational and NoSQL systems. - Partner with Platform and Backend engineers to standardize data interaction patterns, ensuring high-scale, API-driven performance across the entire enterprise cloud. - Partner closely with the Product Management team to influence the product roadmap, translate business requirements into technical specifications, and ensure alignment between product goals and engineering execution. Qualifications - Bachelor's Degree in Computer Science / Master’s or above preferred. - 10+ Years of experience in backend, data, or platform engineering, with a proven track record of solving complex latency and implementation challenges for systems supporting millions of users. - 2+ Years of experience in a Technical Lead or Player-Coach capacity, with demonstrated success managing, mentoring, and steering a small team of engineers while remaining hands-on in the codebase. - Deep, hands-on proficiency with SQL database systems (PostGress), search systems (e.g. Elastic) AND with MongoDB/Atlas, including complex aggregation pipelines, BSON data modeling, sharding, replica sets, and advanced query performance tuning. - Strong experience building Data Access Layers (DAL), custom ODMs, or query translation engines that successfully decouple application logic from underlying storage systems. - High proficiency in Node.js or other major backend languages (Python, Java, or Go) to build high-scale, event-driven architectures. - Direct experience implementing Redis (caching/TTL strategies) and Atlas Search (Lucene) to optimize data retrieval and discovery. - Advanced knowledge of cloud platforms (AWS, Azure, or GCP) and distributed systems, including experience with containerization (Docker/Kubernetes). - Familiarity with SQL-to-NoSQL translation patterns and a background in building internal developer platforms or metadata-driven systems (e.g., no-code/low-code). - An AI-forward mindset: You are an avid user of AI tools and are passionate about exploring how AI can automate workflows, enhance creativity, and increase your personal impact. Benefits - 💻 Work from home with a remote-first community. - 🏝 Unlimited PTO (and the encouragement to use it). - 📝 Student loan payback program. - 🏥 100% employer-covered medical, dental, and vision options available to you and your dependents. - 💸 Flexible Spending Account (FSA). - 🏠 Monthly stipend toward your WFH setup, vacation, development, and more. - 💰 Employer-sponsored 401(k) with contribution match. - 🏋🏻♀️ Subsidized ClassPass Membership. - 🍼 Generous Paid Parental Leave. Hiring Ranges - Tier 1: $238,600 - $298,300. - Tier 2: $219,700 - $274,700. Company Description Unqork embraces a culture of security and privacy awareness by consistently safeguarding sensitive information, adhering to company policies, and actively participating in training and initiatives to protect our data and the privacy of our stakeholders. Unqork is an equal opportunity employer. We will consider all qualified applicants without regard to race, color, nationality, gender, gender identity or expression, sexual orientation, religion, disability or age.
• Lead and provide expert support for data collection, data validation, data visualization, and analytics initiatives • Apply disciplined methodologies for the planning, analysis, design, and development of information systems on an enterprise-wide basis or across a business sector • Develop analytical techniques and methodologies to solve complex business and technical problems • Perform strategic systems planning, business information planning, and business analysis • Organize and analyze large volumes of structured and unstructured data sets using data analytical tools • Locate, access, merge, clean, and standardize data from multiple sources, and develop derived metrics • Create and implement data collection and analysis tools using programming languages such as Python, Databricks, SQL, Scala, R, and Java • Design, script, debug, and analyze data engineering solutions • Implement and create machine learning-based tools and processes • Apply distributed and parallel processing technologies (e.g., Spark) to handle big data analytics tasks involving large data volumes • Perform SQL Server data imports from CSV and TXT files • Leverage Excel and Google Suite for data analysis, reporting, and collaboration • Utilize supporting tools and platforms such as Pentaho (data import/transformation), Azure Data Studio, GitHub, and Smartsheet as needed • Document task requirements, work completed, processes, and technical details thoroughly • Communicate effectively with stakeholders across technical and business teams • Operate independently as a subject matter expert in a fast-paced, entrepreneurial environment
Mediavine is a leading programmatic ad tech partner helping independent publishers build sustainable businesses
Role Description The Data & Analytics team consists of data analysts, data engineers, and analytics engineers working to build the most effective platform and tools to help uncover opportunities and make decisions with data here at Mediavine. A Data Engineer at Mediavine will help build and maintain our data infrastructure, including: - Building scalable data pipelines - Managing transformation processes - Ensuring data quality and security at all steps - Writing and maintaining code in Python and SQL - Developing on AWS - Selecting and using third-party tools like Rundeck, Metabase, and others Essential Responsibilities include: - Create data pipelines that make data available for analytic and application use cases - Develop self-healing, resilient processes - Create meaningful data quality notifications - Lead projects from a technical standpoint, creating project Technical Design Documents - Support data analysts and analytics engineers - Participate in code reviews - Build or implement tooling around data quality, governance, and lineage - Provide next-level support for data issues - Work with data analysts and analytics engineers to standardize transformation logic - Enable analytics engineers and data analysts by providing data modeling guidance Qualifications - 3+ years of experience in a data engineering role - Strong Python skills (understands tradeoffs, optimization, etc.) - Strong SQL skills (CTEs, window functions, optimization) - Experience working in cloud environments (AWS preferred, GCS, Azure) - Experience managing complex dbt environments with hundreds or more flows - Understanding of how to best structure data for analytics - Familiarity with calling APIs to retrieve data - Experience working with DevOps to deploy, scale, and monitor data infrastructure - Scheduler experience either traditional or DAG based - Experience using LM-powered tools for code generation, documentation, and architectural diagramming - Comfortable working with multi-TB cloud data warehouses (Snowflake preferred) - Experience with other DBMS systems (Postgres in particular) - Ability to travel up to approx 15% Requirements - Experience with web analysis such as creating data structures that support product funnels, user behavior, and decision path analysis - Understanding of Snowflake external stages, file formats, and snowpipe - Experience managing the semantic layer in either dbt or Snowflake - Experience with orchestration tools across different technologies and stacks - Knowledge of Ad Tech, Google Ad Manager - The ability to make your teammates laugh - Familiarity with event tracking systems (Snowplow, etc.) - Experience with one or more major BI tools (Omni, Sigma, Metabase, etc.) Benefits - 100% remote - Comprehensive benefits including Medical, Dental, Vision, Disability, and Life Insurance - 401(k) with company matching - Generous PTO - Wellness initiatives and employer-sponsored mental health resources - Professional development opportunities - Inclusive, collaborative, and entrepreneurial company culture
Global energy think tank that uses data-driven insights to shift the world to clean electricity.
Role Description Use your coding and data skills to work on the most important challenge of our time: shifting the world to clean energy. Ember publishes the best-in-class dataset on global electricity generation and the data team is growing as we expand our datasets to new areas such as installed renewable capacity, price, battery storage, grids and flexibility, EV and heat pump deployment. We are looking for someone to use their data and coding skills to ensure we can quickly gather and curate data from new sources, as well as helping to run, maintain and document existing data pipelines. This role offers an exciting opportunity to learn from a knowledgeable and passionate team of engineers and analysts while applying your development skills towards the clean energy transition. Key Responsibilities - Develop new ETL scripts using Python to gather and validate data from a variety of sources e.g. APIs, web scraping. - Work with our data engineering team to deploy ETL scripts within our orchestrated data platform based on Dagster and BigQuery. - Help run, maintain, and improve existing data pipelines. - Help ensure that our pipelines are written using best coding and data practices. - Help ensure Ember’s data and output are of the highest standard. Qualifications - At least one year experience developing and deploying Python code. - Experience working with SQL databases. - Numerate and data literate, with excellent data extraction and transformation skills. - A thoughtful and selective approach to the use of AI coding tools and the ability to critically evaluate their outputs. - Fluent in spoken and written English. - Passionate about clean energy. - Driven and keen to learn. - Systematic with careful attention to detail. - Ability to work as part of a remote international team. Requirements - Experience developing data pipelines on an orchestration platform such as Dagster (preferred), Airflow, dbt or Prefect. - Experience with version control software such as Git. - Experience working on cloud platforms, such as GCP (preferred), AWS or Azure. - Experience working with business users to turn research questions into specific data requirements, and developing to those requirements. - Other language skills. - Previous experience within the power sector or clean energy sector. Benefits - We operate a nine-day fortnight meaning our full-time staff are given every other Friday off work with no reduction in pay. - 25 days holiday, plus UK bank holidays (unless local statutory minimums are higher) and for each year that you're part of the team at Ember you'll receive an additional day of holiday, up to a maximum of 5 additional days. - Generous paid maternity and paternity leave. - Flexible working conditions, including the opportunity for part-time work and home working. - Access to a local working space can also be arranged for employees. - Free annual eye tests. - Access to a counselling service. - Funding and allocated time for your training and development. - Paid volunteer day. - Four paid days off to enable low carbon travel. - Time off to donate blood. Company Description Ember is an independent, not-for-profit energy think tank that aims to accelerate the clean energy transition with data and policy. We gather, curate and analyse data on the power sector and coal mine methane emissions, and use our findings to improve energy and climate policy. See our work at ember-energy.org and @ember_energy .
Anteriad is an advertising services company that specializes in providing full-funnel business-to-business (B2B) marketing solutions to help its clients drive g
Title: Data Engineer Location: remote Job Description: Come Join Our Team At Anteriad and innovate the way B2B marketers make data-driven business decisions. About Anteriad We are not just another B2B solution provider. We're problem solvers. We believe that data is the key to unlocking effective solutions that span a range of marketing challenges - from customer acquisition to demand generation to account-based marketing. Data is at the core of everything we do. Our team works tirelessly to create powerful solutions that drive real results for our clients. Whether it's through innovative technology or deep analysis, we're committed to finding the best path to growth for every one of our customers. Why Join Our Data Integration Team? This is an excellent opportunity for an intelligent, energetic, and self-motivated individual to play a vital role within a growing part of Anteriad. As our Data Engineer, you will have an important role in receiving, organizing, and loading data into Anteriad’s Data Warehouse to be used by our clients and throughout the Anteriad organization. As an integral part of the Data Integration team, you will play a key role in building, managing, and optimizing data pipelines that support our marketing and analytics efforts. You will be a professional with deep expertise in SQL and hands-on experience with SSIS and cloud-based data solutions, especially within the Azure ecosystem. This role may require 1-4 on-site meetings at our NYC office per year. You must be willing to attend if scheduled. This role is not eligible for sponsorship, including current OPT and/or partner VISA status. Anteriad means “always moving forward” and we apply that to our company culture by tirelessly promoting an environment that allows our employees to thrive: - Work from home - Flexible PTO - Training & development with unlimited access to Percipio LMS - Mix of collaborative & independent work - Community outreach via Anteriad Cares - encouraging staff to take time to volunteer - Professional mentoring program - career guidance from leadership - Employee Resource Groups - collaborate with others that share your passions! - Benefits We Bring to You: - Comprehensive medical (choice of 3 plans), dental and vision coverage - Company paid short-term disability, long term disability, and life insurance - Optional supplemental life, accident, and critical illness insurance plans - 401K with company match - Flexible PTO and generous holiday schedule - Fully paid primary caregiver leave (12 weeks) & parental bonding leave (2 weeks) - What You’ll Do - Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions. - Design, develop, and maintain data integration solutions using Microsoft SQL Server, Azure Data Factory, Azure Databricks, Microsoft Fabric, and related Azure services. - Build, manage, and optimize ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric Pipelines, including pipeline orchestration, parameterization, scheduling, monitoring, and error handling. - Develop and maintain data transformation logic using Azure Databricks notebooks and Microsoft Fabric notebooks, with a focus on performance, scalability, reusability, and operational reliability. - Design and implement data ingestion, transformation, validation, and delivery processes across structured, semi-structured, and external data sources. - Develop and optimize data integration processes utilizing Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, Microsoft Fabric Lakehouses, Warehouses, Pipelines, and Notebooks. - Build and maintain SQL-based data models, stored procedures, views, automation scripts, and database objects to support operational and analytical workloads. - Support the modernization and migration of legacy data integration processes from SSIS and on-premises platforms to cloud-based Azure and Microsoft Fabric architectures. - Design and implement reusable pipeline patterns, data quality checks, validation controls, logging, alerting, and performance monitoring processes. - Support new client onboarding efforts by designing and implementing reliable data ingestion, transformation, reconciliation, and validation workflows. - Troubleshoot and resolve data pipeline, data quality, performance, and integration issues in collaboration with teams across Intelligence & Analytics. - Design, develop, and maintain datasets, semantic models, and data structures that support reporting, analytics, and visualization solutions across Power BI, Excel, Microsoft Fabric, and other business intelligence platforms. - Contribute to data engineering standards, documentation, best practices, and reusable frameworks that improve scalability, maintainability, and operational efficiency. - Research, evaluate, and recommend emerging technologies and platform capabilities that improve data architecture, automation, performance, and reliability. - What You’ll Bring - 3+ years of experience in data engineering, data integration, business intelligence engineering, or a related technical role. - 3+ years of experience writing, optimizing, and troubleshooting SQL, including T-SQL, stored procedures, views, indexing strategies, and query performance tuning. - Hands-on experience designing, building, and supporting ETL/ELT pipelines using Azure Data Factory and/or Microsoft Fabric Pipelines. - Hands-on experience developing data processing and transformation logic using Azure Databricks notebooks, Microsoft Fabric notebooks, PySpark, Spark SQL, Python, or similar technologies. - Strong Microsoft SQL Server and relational database design principles skills. - Experience with Azure data platform services such as Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, and related cloud data services. - Strong knowledge and in depth work with Microsoft Fabric components such as Pipelines, Notebooks, Lakehouses, Warehouses, Dataflows, and semantic models. - Experience building reliable data ingestion and transformation processes from APIs, flat files, databases, web services, cloud storage, and other external data sources. - Hands on experience implementing data validation, reconciliation, monitoring, logging, and alerting processes for production data pipelines. - Experience supporting production data workloads, including troubleshooting failures, optimizing performance, and improving pipeline reliability. - Prior experience modernizing or migrating legacy ETL processes from SSIS, SQL Server, or on-premises environments to Azure or Microsoft Fabric is strongly preferred. - Bachelor’s degree in Computer Science, Information Technology, Data Analytics, a related field, or equivalent professional experience. - Power BI, semantic models, or other data visualization and analytics tools experience is a plus. - Experience with Customer Data Platforms, CDPs, database marketing, marketing analytics, or client data onboarding environments is a plus. - Working knowledge with AWS or Google Cloud Platform is a plus. - Strong analytical, problem-solving, and critical thinking skills. - Excellent verbal and written communication skills, with the ability to explain technical concepts to both technical and non-technical audiences. - Ability to work independently on moderately complex data engineering tasks while collaborating effectively in a team-oriented environment. - Our Values: - Lead & Learn We lead with unrivaled vision, innovation and execution, always learning and embracing new ways of doing things to stay out in front - Collaborate & Celebrate We build great things when we work together as one Anteriad team, celebrating our achievements – both great and small – along the way - Innovate & Inspire We are always looking for bold new ways to exceed the expectations of our customers and to inspire each other to even greater success - Do More & Do Good We go above and beyond in the service of our clients and colleagues, and the communities where we live - Notice to California Applicants: We collect and process personal information as described in our California Applicant Privacy Notice, in compliance with the California Consumer Privacy Act (CCPA/CPRA). Please review the notice here: Anteriad Privacy Policy
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Python, SQL, Azure, Data Engineering, AWS, ETL
