Senior Azure Data Engineer

• Your profile:

  • at least 8 years of professional experience in Data Engineering, including ownership of production-grade data pipelines,
  • strong, demonstrable hands-on experience with Microsoft Azure and Databricks,
  • advanced SQL and Python skills,
  • strong experience designing, building, and operating data pipelines and analytical data products,
  • a good command of modern data-platform and lakehouse principles, including medallion architecture and dimensional modelling for reporting,
  • experience with software engineering and DataOps practices, including version control, automated testing, CI/CD, deployment, monitoring, and incident management,
  • experience with SRE practices and continuous operational improvements,
  • strong stakeholder communication skills and the ability to collaborate across Data, Architecture, Product, and Engineering teams,
  • data modelling skills and the ability to develop a holistic view of different data scopes and business objectives before making build decisions,
  • being able to work autonomously, make sound technical decisions, and document them clearly.

  Nice to have:

  • experience with data governance, lineage, and access-control practices in Databricks, including Unity Catalog,
  • experience with payment or transaction data,
  • experience working in distributed international teams.

  Recruitment Process:

  CV review – HR call – Interview – Client Interview – Decision

,[designing, building, testing, and deploying scalable data pipelines for reporting and analytics use cases,, creating new, production-ready pipelines supporting priority reporting use cases,, reviewing existing reporting pipelines and refactoring them to improve reliability, performance, maintainability, and observability,, maintaining new and existing pipelines to ensure data assets are reliably delivered on a daily basis,, working with Data professionals, Data Architects, Product Managers, and Engineering Managers to translate reporting needs into robust technical solutions,, contributing hands-on to the onboarding of Core Products data workloads onto the Data Platform,, ensuring pipelines are aligned with the architecture, governance, security, and engineering standards of the Data Platform,, ensuring compliance with platform standards for data modelling, code quality, testing, CI/CD, documentation, security, and monitoring,, owning SRE practices for data pipelines and products,, diagnosing data incidents and pipeline failures, identifying root causes, and implementing durable corrective actions,, documenting data flows, dependencies, transformation logic, and operating procedures,, ensuring clear documentation, monitoring, and operational ownership to support maintainability and reliable handover,, sharing knowledge and engineering practices with the Core Products data team and contributing to its long-term autonomy.] Requirements: Python, Azure, CI/CD, SQL, Spark, Dataops, SRE, Databricks Tools: Jira, Confluence, SharePoint, Agile, Scrum. Additionally: Training budget, Private healthcare, Multisport, Integration events, International projects, Mental health support, Referral program, Modern office, Canteen, Free snacks, Free beverages, Free tea and coffee, No dress code, Playroom, In-house trainings, In-house hack days, Normal atmosphere :).