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.