About this role
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
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.