Hello, let’s meet! Who We Are While Xebia is a global tech company, our journey in CEE started with two Polish companies – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started. What We Do We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data and AI solutions, and cutting-edge applications to shape the future of tech. Our clients include McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland! Beyond Projects What makes Xebia special? Our community. We support tech communities, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow. What sets us apart? Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself. You will be: - developing and automating tools within the Data Platform, including: - clickstream data processing, - building and evolving an ID Graph service, - implementing and enhancing Self-Service Analytics solutions, - designing, building, and maintaining effective streaming data pipelines, - supporting product, engineering, and analytics teams in building data-driven products and services, - solving technical and analytical issues reported via internal communication channels (e.g. Slack, email, incident management tools), - applying software engineering best practices such as Clean Code, TDD, and CI/CD, - participating in an on-call / incident response rotation. Your profile: - strong commercial experience as a Senior Data Engineer, - very good programming skills in Python and one of JVM languages: Java, Kotlin, or Scala, - proven experience in building and maintaining streaming data pipelines, - hands-on experience with Google Cloud Platform, especially BigQuery, Cloud Composer, Dataproc, Dataflow, Cloud Run, - advanced knowledge of SQL and dbt, - solid understanding of software engineering best practices: TDD, Clean Code, CI/CD pipelines, - very good command of Linux/Unix environments, - experience with Docker and daily use of Git or other version control systems, - strong teamwork skills and a proactive, positive attitude, - fluent Polish and English at B2+ level, - readiness to participate in an on-call rotation (24/7, 7 dys per week / every 5-8 weeks) - practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery. Work from the European Union region and a work permit are required. Nice to have: - experience with Spring Framework, - knowledge of Apache Beam, Scio, and Google Dataflow, - practical experience with Apache Flink, - experience with Infrastructure as Code, especially Terraform, - experience with Spark or PySpark (not necessarily in a Hadoop environment), - experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work, - interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches. Recruitment Process: - CV review – HR call – Interview – Client Interview I - Client Interview II – Decision

Role Description The Senior Data Engineer is responsible for designing, implementing, and maintaining enterprise-scale data architecture solutions. This role designs and develops a greenfield data lakehouse system, including data ingestion pipelines, storage optimization, and high-performance query APIs. The position requires hands-on technical implementation combined with strategic architectural design skills and English speaking individual. Data Architecture Design - Understand PROBIS data model, identify bottlenecks and translate into actionable designs - Design a modern data lakehouse architecture for greenfield implementation - Architect scalable data storage and processing solutions using Azure ecosystem and applicable open source components - Design the best stack for the job, considering data sovereignty and storage requirements in target markets Technical Implementation - Implement data ingestion pipelines from existing postgres database systems and integrations - Improve the .net based data access of existing postgres system - Build and verify high-performance query APIs on top of the greenfield design, enabling orders of magnitude growth in data volume, with improved performance - Develop and optimize data transformation processes - Set up monitoring and observability for reliable live operation System Integration - Integrate the data lakehouse with existing enterprise systems - Design and implement performant query engines for user interfaces - Ensure data consistency and quality across integrated systems Documentation and Compliance - Execute performance and consistency testing under increased loads - Collect evidence and document the architecture - Ensure compliance and support necessary certification processes Qualifications - Minimum 6 years of experience in data engineering - Minimum 4 years of hands-on experience with Microsoft Azure data services - Proven track record of shipping performant data projects on Azure / Postgres / Data Factory / Databricks Requirements - Expert proficiency in Microsoft Azure data platform (Synapse, Data Factory, SQL Databases, Data Lake) - Good .NET Core development skills - Strong SQL and database (psql) optimization capabilities - Experience with data modeling techniques and methodologies - Ideally, experience with sovereign data solutions including Spark based data warehousing - Knowledge of ETL/ELT processes and data pipeline design Benefits - Opportunity to work with cutting-edge AI, cloud technologies and tools - Full access to our comprehensive toolset - Flexible remote work options with home office capability - International, team-oriented atmosphere with flat hierarchies - Culture of open feedback and quick decision-making processes - Regular team and company events - Opportunity to shape the technical direction of a growing PropTech company - Highly professional and high-skilled Senior Developers

**MUST RESIDE IN CENTRAL OR EASTERN TIME ZONE** Work at Home Opportunity Data Engineer - Full-time BELAY is a growing and vibrant, Atlanta, GA-based company that offers virtual staffing solutions in the areas of Virtual Assistants, Marketing Assistants, and Financial Specialists. We are a fast-paced team of high performers that work extremely hard but also know how to have a great time. Culture is a top priority and our values are lived out daily. Who is BELAY? Click here and enjoy! Below are the position requirements. Job purpose The Data Engineer will play a critical role in designing and maintaining Belay’s modern data stack. This role is responsible for building reliable, scalable data pipelines, optimizing warehouse performance, and implementing robust orchestration frameworks. The ideal candidate is highly technical, systems-minded, and experienced in Snowflake-centric environments with strong PostgreSQL and data orchestration expertise. You should be comfortable owning data infrastructure end-to-end and partnering cross-functionally with analytics, finance, and engineering teams. Duties and responsibilities As a BELAY Corporate Team member, you will professionally represent the company in all virtual and in-person interactions. You are expected to exemplify our mission, vision and core values daily, fostering a collaborative and positive team environment. Key Responsibilities Data Architecture & Engineering - Design, build, and maintain scalable ELT/ETL pipelines - Develop and optimize data models in Snowflake/PostgreSQL - Ensure data reliability, integrity, and performance across the platform - Implement best practices for data warehousing and pipeline efficiency Orchestration & Workflow Management - Build and manage workflows using Apache Airflow/Dagster - Design robust orchestration frameworks for batch and near-real-time pipelines - Monitor pipeline health and implement proactive alerting - Troubleshoot and resolve data pipeline failures quickly Database Management - Work extensively with Snowflake and PostgreSQL for source systems and operational workloads - Optimize queries and database performance - Design and maintain data ingestion patterns from Postgres to Snowflake Performance & Scalability - Tune Snowflake workloads for cost and performance efficiency - Implement partitioning, clustering, and workload management strategies - Continuously improve pipeline speed and reliability Collaboration & Strategy - Partner with analytics, finance, and product teams to support reporting needs - Translate business requirements into scalable data solutions - Mentor junior data engineers and promote best practices - Contribute to the long-term data architecture roadmap Qualifications This role requires a motivated and trustworthy self-starter with strong communication and technological skills who thrives both independently and on a team. Our ideal corporate team member is flexible, creative, well-organized and ready to roll up their sleeves to get the job done! Required Qualifications - 5+ years of experience in data engineering or related field - Strong hands-on experience with Snowflake - Strong experience with PostgreSQL - Proven expertise with Apache Airflow or Dagster and workflow orchestration - Experience building and maintaining modern ELT/ETL pipelines - Advanced SQL skills and strong data modeling experience - Experience with orchestration and pipeline monitoring best practices - Familiarity with cloud data architectures (AWS, GCP, or Azure) - Strong problem-solving and performance tuning skills - Excellent communication and documentation abilities Preferred Qualifications - Experience with dbt or similar transformation frameworks - Experience with real-time or streaming pipelines - Infrastructure-as-code experience (Terraform or similar) - Experience supporting finance or operational analytics teams - Background in high-growth or services-based companies Working conditions BELAY Corporate offers full-time remote work, requiring a dedicated, distraction-free home office for standard Monday-Friday business hours, with occasional travel for some roles. As a full-time/part-time, exempt/non-exempt W-2 employee, you'll join a vibrant, award-winning company culture where you're a valued, engaged team player in a thriving organization. Physical requirements This position does not have any physical requirements at this time. Salary Range $110,000 - $150,000 DISCLAIMER: We’ve recently seen job postings claiming to be from BELAY that aren’t affiliated with our company. Please be sure to only apply to our positions on https://belaysolutions.com/jobs/ and only reply to emails ending in @belaysolutions.com.

• Monitoring Checks: Perform regular monitoring of data processes to ensure smooth operation and identify potential issues. • Incident Support and Solving: Provide prompt support for incidents, troubleshoot problems, and implement solutions to minimize downtime. • Continuous Improvement: Identify opportunities for improving the production environment and implement changes to enhance efficiency and reliability. • Failure Management: Proactively avoid and capture failures in data processing to ensure uninterrupted service. • Communication & Documentation: Maintain clear and effective communication with stakeholders and document processes, incidents, and solutions. • KPI Monitoring: Monitor key performance indicators, including data set availability percentages, to ensure service quality. • Tickets Management: Manage tickets by creating, assigning, following up, and resolving issues in a timely manner. • Knowledge Base Management: Develop and maintain a comprehensive knowledge base to support ongoing operations and incident resolution.