Senior Azure Data Engineer
Summary
Build and maintain Azure-based data pipelines and analytics infrastructure using Databricks, Data Factory, and PySpark to process large-scale datasets for enterprise clients.
SNI is serving as a trusted IT Outsourcing partner in line with the needs of World's most prestigious firms and carried out successful projects worldwide.
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, 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.
Skills:
5+ years of data engineering experience with a focus on enterprise ETL/ELT pipelines and cloud data platforms.
Mandatory certifications: Certified Azure Data Engineer and Databricks Certified Data Engineer.
Core Azure expertise: Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), and MS Cloud SQL Server.
Strong programming proficiency in Python, PySpark, Spark SQL, or Scala/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 both English and Polish.
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