Senior Databricks Data Engineer

Senior Databricks Data Engineer - Pune, India

We are seeking a Senior Databricks Data Engineer to provide technical leadership for a large-scale enterprise BI modernization initiative. This is not a lift-and-shift migration effort. The role will lead the systematic transformation of a complex Microsoft BI ecosystem (SSIS, SSAS, SSRS) into scalable, governed Databricks Lakehouse architecture.

The Senior Engineer will establish architectural standards, define repeatable migration frameworks, , and guide the modernization of thousands of legacy data assets into reusable, high-performance Spark-based solutions. This individual combines deep hands-on data engineering expertise with architectural thinking, mentorship capability, and strong cross-functional collaboration skills.

Key Responsibilities

• Lead the architecture and implementation of enterprise-scale data pipelines on Databricks.
• Serve as technical lead for the migration of a ~20TB Microsoft SQL Server data warehouse to the Databricks Lakehouse Platform.
• Design and implement reusable Spark-based pipeline frameworks to replace thousands of SSIS workflows.
• Deconstruct SSAS cube logic and redesign it into Lakehouse-native semantic models.
• Replace legacy SSRS reporting ecosystems with modern, governed analytics layers.
• Rebuild dimensional models within Delta Lake using scalable Lakehouse design patterns.
• Define data modeling standards, ingestion frameworks, CI/CD processes, and operational best practices.
• Implement and enforce Medallion architecture standards (Bronze/Silver/Gold) with performance optimization and governance controls.
• Optimize Spark workloads for scalability, reliability, and cost efficiency.
• Implement governance, lineage, security, and monitoring using Unity Catalog and related platform tooling.
• Mentor engineers, conduct architectural reviews, establish and maintain engineering standards.
• Partner with BI, analytics, and AI/ML teams to enable advanced analytics and downstream use cases.
• Influence platform roadmap and architectural decisions.

Required Qualifications

• Bachelor s or master s degree in computer science, engineering, or related field.
• 8 - 12 years of data engineering experience.
• 5+ years of hands-on experience building and operating production workloads on Databricks.
• Deep expertise in SQL, PySpark, and distributed data processing.
• Demonstrated leadership in structured enterprise BI modernization programs.
• Proven experience replacing SSIS-based ETL with scalable Spark-based frameworks.
• Strong understanding of SSAS cube architecture and semantic layer modernization.
• Experience designing and operating high-volume, enterprise-grade analytical data platforms.
• Strong knowledge of Delta Lake, Lakehouse and Medallion architectures, data versioning, and Workflows/Jobs orchestration.
• Experience implementing CI/CD, testing frameworks, and operational reliability for data platforms.
• AWS-based Databricks experience strongly preferred.

Preferred Skills

• Experience designing semantic layers and BI integrations (Power BI preferred).
• Exposure to Databricks AI/ML capabilities (MLflow, feature engineering, feature stores).
• Experience establishing enterprise migration patterns across distributed teams.
• Prior technical leadership experience in global or multi-team environments.
• Strong stakeholder engagement and communication skills.
• 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.