Senior Data Engineer

Information about the project:

• Industry: IT

• Location: Remote

• Rate: up to 160 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.

Main 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.

Key Requirements:

• 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 Have:

• 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.