Looking for Senior Databricks Data Engineer In Pune, IN Onsite Job :: Offshore

Senior Databricks Data Engineer Pune, India 12+ Months Contract WebEx Interview

Job Description:

We are seeking a Senior Databricks Data Engineer to provide technical leadership on a major data platform transformation initiative. This role will lead and execute the migration of a large-scale Microsoft SQL Server data warehouse ecosystem—including SSIS, SSAS, and SSRS—onto the Databricks Lakehouse Platform. The ideal candidate combines deep hands-on data engineering expertise with architectural thinking and mentorship capabilities.

Key Responsibilities

Lead the design and implementation of enterprise-scale data pipelines on Databricks. Serve as a technical lead for the migration of a ~20TB SQL Server data warehouse to Databricks. Architect migration strategies for hundreds of tables, thousands of SSIS jobs, and complex reporting workloads. Redesign legacy ETL and cube-based architectures into modern Lakehouse patterns. Define data modeling standards, ingestion frameworks, and transformation best practices. Optimize Spark workloads for performance, scalability, and cost efficiency. Mentor and guide data engineers across multiple experience levels. Partner with BI, analytics, and AI/ML teams to enable advanced analytics use cases. Implement data governance, security, lineage, and monitoring using Unity Catalog and platform tooling. Translate business requirements into scalable technical solutions. Influence platform roadmap, engineering standards, and architectural decisions.

Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 8–12 years of overall data engineering experience. 5+ years of hands-on experience building production workloads on Databricks. Deep expertise in SQL, PySpark, and distributed data processing. Proven leadership in migrating enterprise SQL Server data warehouses to cloud platforms. Strong experience replacing SSIS-based ETL with modern Spark-based pipelines. Solid understanding of SSAS cube architectures and modernization approaches. Experience designing highly reliable, high-volume analytical data platforms. Strong knowledge of Delta Lake, Lakehouse and Medallion architectures, data versioning, and Workflows/Jobs orchestration. Experience implementing CI/CD, testing, and operational best practices for data pipelines. Primary experience with AWS-based data platforms strongly preferred.

Preferred Skills Experience designing semantic layers and BI integrations (Power BI preferred). Exposure to Databricks AI/ML capabilities such as MLflow and feature stores. Experience operating in environments aligned with Databricks-recommended engineering patterns. Databricks certification is a plus. Prior technical leadership experience in distributed or global teams. Strong communication and stakeholder engagement skills.