Senior Azure Data Engineer

Responsibilities

• Design and construct data structures, DDLs, tables, and views across MS Cloud SQL Server and Data Lake environments.
• Develop Azure Databricks notebooks and PySpark/Spark SQL jobs to aggregate, join, and output standardized data formats (SFFs).
• Configure automated ingestion frameworks to streamline data loading across staging and Data Lake Core (DLC) layers.
• Build, optimize, and maintain large-scale batch and real-time data pipelines using Azure Data Factory and Databricks.
• Monitor performance, tune complex SQL queries, and implement automation across data integration workflows.
• Support data governance by tracking data consumption patterns, testing pipeline outputs, and promoting curated datasets to the data catalog.
• Apply CI/CD practices and collaborate within cross-functional Agile/Scrum teams to deliver project estimates and technical solutions.

Requirements

• 5+ years of data engineering experience focused on enterprise ETL/ELT pipelines and cloud data platforms.
• Certified Azure Data Engineer and Databricks Certified Data Engineer certifications.
• Expertise in Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), and MS Cloud SQL Server.
• Strong programming proficiency in Python, PySpark, Spark SQL, Scala, or Java.
• Advanced SQL skills for data manipulation, query optimization, and relational database management.
• Experience with legacy MS SQL stack technologies (SSIS, SSRS) and reporting tools (Power BI).
• Experience with automated ingestion frameworks, big-data processing, and CI/CD delivery practices in Agile environments.
• Full professional fluency in English and Polish.