Databricks Data Engineer - Pune, India

We are seeking a Databricks Data Engineer to join our growing data engineering team in Pune, India, supporting a structured enterprise BI modernization program. This role will play a key part in the systematic transformation of a complex, enterprise-grade Microsoft SQL Server ecosystem (SSIS, SSAS, SSRS) into scalable, governed Databricks Lakehouse architecture.

The ideal candidate brings strong hands-on experience with Databricks data engineering capabilities and will work within defined migration frameworks to modernize ETL pipelines, semantic models, and reporting assets into reusable, Spark-based solutions. While exposure to Databricks AI/ML capabilities is a plus, the primary focus of this role is building scalable, reliable data pipelines and analytics workloads aligned with Lakehouse best practices.

Key Responsibilities

- Design, build, and optimize scalable data pipelines using Databricks (Spark, Delta Lake, Unity Catalog).
- Participate in the migration of a ~20TB on-prem Microsoft SQL Server data warehouse to Databricks under defined architectural standards.
- Convert hundreds of SQL Server tables and thousands of SSIS workflows into standardized, reusable Spark-based pipeline patterns.
- Re-engineer legacy SSIS ETL processes into Databricks notebooks, workflows, and orchestration frameworks aligned with Medallion architecture principles.
- Support modernization of SSAS cube-based analytics into Lakehouse-native semantic models and assist in transitioning legacy SSRS reporting to contemporary governed reporting layers.
- Rebuild and optimize dimensional models within Delta Lake to support scalable analytics workloads.
- Implement data quality, validation, reconciliation, audit, and migration controls throughout the modernization process.
- Optimize Spark performance, partitioning strategies, and cost efficiency across large-scale datasets.




- Apply governance, security, lineage, and access-control standards using Unity Catalog.
- Collaborate with analytics, BI, and AI/ML teams to enable downstream reporting and advanced analytics use cases.
- Contribute to reusable frameworks, documentation, and engineering best practices.

Required Qualifications

- - Bachelor s degree in computer science, engineering, or a related field.
- 5 - 7 years of data engineering experience.
- Hands-on experience with Databricks (AWS preferred; Azure acceptable).
- Strong proficiency in Spark (PySpark and/or Scala) and SQL.
- Experience participating in migration of on-prem SQL Server data warehouses to cloud-based platforms.
- Experience converting SSIS-based ETL pipelines into Spark-based data engineering solutions.
- Experience working within structured migration or enterprise modernization initiatives (not solely lift-and-shift projects).
- 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.

Preferred Skills

- Experience modernizing SSAS cube-based reporting solutions into Lakehouse-native semantic models.
- Exposure to Databricks SQL Warehouses and BI integrations (Power BI preferred).
- Working knowledge of Medallion architecture and Databricks best practices for scalable Lakehouse implementations.
- Familiarity with MLflow, feature engineering, or AI-enablement within Databricks.
- Databricks certification is a plus.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Databricks Data Engineer (Pune)
🏢 PARKAR GLOBAL TECHNOLOGIES
📍 Pune