Data Engineer
Posted Updated 56
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Summary
Zensar is hiring a Data Engineer in India to build finance-domain (capital & tax) data products on the Microsoft data stack: SQL Server/T-SQL, Azure Data Factory, Databricks, and Microsoft Fabric lakehouse using PySpark and Delta Lake. Work spans CDC ingestion, Power BI semantic models, governance, and mentoring junior engineers.
Zensar Technologies Limited is seeking a highly skilled Data Engineer to engineer and deliver Finance (Capital & Tax) domain‑aligned data products within a centrally governed Microsoft Data Platform. You will modernize legacy SQL workloads into scalable Spark‑based Lakehouse datasets, manage ADF pipelines, Databricks notebooks, and Azure Analysis Services cubes, and ensure data products are version‑controlled, tested, monitored, and continuously improved.
- Build and maintain bronze, silver, and gold lakehouse layers in Microsoft Fabric and Databricks.
- Develop ingestion and transformation pipelines using notebooks and PySpark.
- Implement incremental loading and change data capture (CDC) from on‑prem SQL to Fabric/Databricks.
- Optimize Delta tables for performance and cost efficiency.
- Create and sustain Azure Data Factory pipelines and Azure Analysis Services cubes.
- Own data products as managed assets: version control, testing, monitoring, and continuous improvement.
- Ensure datasets comply with defined data contracts, governance, and platform standards.
- Collaborate with business stakeholders, analysts, and the central Data Platform team.
- Design and optimize semantic models for enterprise analytics platforms such as Power BI.
- Mentor junior engineers and champion architectural standards and modern technologies.
- 6+ years of hands‑on data engineering experience in SQL‑heavy or enterprise data environments.
- Deep expertise in Microsoft SQL Server and advanced T‑SQL development, including query optimization.
- Practical experience with Microsoft Fabric, Lakehouse architecture, and Delta Lake.
- Proficiency in Spark (PySpark preferred) and Python notebooks for distributed data transformation.
- Experience with Azure Data Factory, Databricks, Azure Analysis Services, ADLS Gen2, and Purview.
- Strong knowledge of dimensional modeling (Kimball) and semantic model design for Power BI.
- Proven ability to implement incremental loading and CDC patterns in hybrid environments.
- Familiarity with CI/CD pipelines, testing frameworks, monitoring, and data governance principles.
- Background in financial services, banking, or capital markets.
- Microsoft certifications (Azure Data Engineer, Fabric) and excellent facilitation, presentation, and influencing skills.