Posted 25 May, 2026
Databricks Data Engineer Pune, India
EDI Staffing
Pune, IN
Full Time
Reference: 26-00087-71-2
Databricks Data Engineer Pune, India
We are seeking a Databricks Data Engineer to join our growing data engineering team in Pune, India. This role will play a key part in a large-scale modernization initiative to migrate a complex, enterprise-grade Microsoft SQL Server data warehouse ecosystem to the Databricks Lakehouse Platform. The ideal candidate has strong hands-on experience across Databricks data engineering capabilities, with exposure to AI/ML features being a plus, while maintaining a core focus on scalable, reliable data pipelines and analytics workloads.
Key Responsibilities
We are seeking a Databricks Data Engineer to join our growing data engineering team in Pune, India. This role will play a key part in a large-scale modernization initiative to migrate a complex, enterprise-grade Microsoft SQL Server data warehouse ecosystem to the Databricks Lakehouse Platform. The ideal candidate has strong hands-on experience across Databricks data engineering capabilities, with exposure to AI/ML features being a plus, while maintaining a core focus on scalable, reliable data pipelines and analytics workloads.
Key Responsibilities
- Design, build, and optimize scalable data pipelines using Databricks (Apache Spark, Delta Lake, Unity Catalog).
- Participate in the migration of a ~20TB compressed on-prem Microsoft SQL Server data warehouse to Databricks.
- Convert and modernize hundreds of SQL Server tables, thousands of SSIS jobs, and downstream SSRS/SSAS workloads.
- Re-engineer SSIS ETL processes into Databricks notebooks, workflows, and orchestration frameworks.
- Support migration or redesign of cube-based analytics (SSAS) into Databricks SQL, Delta tables, and modern semantic models.
- Implement data quality, validation, reconciliation, and audit controls during migration.
- Optimize performance and cost through efficient Spark usage, partitioning, and query tuning.
- Collaborate with analytics, BI, and AI/ML teams to enable downstream reporting and advanced analytics.
- Apply data governance, security, and access-control standards using Unity Catalog.
- Contribute to reusable frameworks, documentation, and platform best practices.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 4 7 years of overall data engineering experience.
- Hands-on experience with Databricks on AWS (preferred); Azure experience acceptable.
- Strong proficiency in Spark (PySpark and/or Scala) and SQL.
- Proven experience migrating on-prem SQL Server data warehouses to cloud-based data platforms.
- Experience converting SSIS-based ETL pipelines into Spark-based data engineering solutions.
- Solid understanding of data warehousing concepts, dimensional modeling, and analytical workloads.
- Experience with Delta Lake, incremental processing patterns, and data versioning.
- Familiarity with Databricks Workflows, Jobs, and production-grade deployments.
- Practical experience with performance tuning and large-volume data processing.
- Experience modernizing SSAS cube-based reporting solutions.
- Exposure to Databricks SQL Warehouses and BI integrations (Power BI preferred).
- Working knowledge of cloud-native data engineering practices aligned with Databricks best practices.
- Familiarity with MLflow, feature engineering, or AI-enablement within Databricks.
- Experience working in environments that follow Databricks-recommended data engineering patterns.
- Databricks certification is a plus.
