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Senior Data Engineer

Summary

Design and build scalable ETL/ELT pipelines using Python, SQL, Spark, and Databricks to process and transform data efficiently for analytics and reporting.

Information about the project:

  • Location: Remote

  • Rate: up to 170 pln/h net + VAT, B2B

  • Project languages: Polish, English

Summary: The Senior Data Engineer will play a crucial role in designing and building scalable ETL/ELT pipelines to support the organization’s data needs, focusing on optimizing data transformations and ensuring robust data architecture.

Responsibilities:

  • Design and build optimized ETL/ELT pipelines for efficient data processing.

  • Utilize advanced Python and SQL skills for scalable data transformations.

  • Implement and optimize data processing frameworks using Apache Spark and Databricks.

  • Work with Azure data services, including ADF/Synapse Pipelines and Azure SQL/Synapse.

  • Manage data governance and access control through Unity Catalog.

  • Architect modern data models, utilizing concepts such as Medallion and Data Vault.

  • Deploy and maintain large-scale cloud-based data platforms.

  • Adhere to DevOps practices for CI/CD in automated pipeline deployment.

  • Communicate effectively in English, both in writing and speaking.

Must Haves:

  • 5+ years of experience in data engineering with a strong background in designing and building ETL/ELT pipelines.

  • Expert-level Python and SQL skills, including building optimized, scalable data transformations.

  • Advanced hands-on experience with Apache Spark & Databricks, including Delta Lake.

  • Strong experience with Azure data services (ADF/Synapse Pipelines, ADLS, Azure SQL/Synapse).

  • Practical knowledge of Unity Catalog and governance models.

  • Deep understanding of modern data architecture patterns.

  • Experience designing and implementing cloud-based, large-scale data platforms.

  • Strong familiarity with Git, CI/CD, DevOps practices, and automated pipeline deployment.

  • Fluency in English (writing and speaking).

Nice to Haves:

  • Openness to learning and working with AI technologies (including agentic frameworks, text 2 sql).

  • Ability to support or collaborate on ML/DS workflows.

  • Exposure to machine learning lifecycle tools (MLflow, Feature Store).

  • Interest in contributing to the evolution of our Azure Data & Analytics Platform.

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