Technical Lead – Data Platform Services Databricks-12 to 15 yrs -Mumbai

• Lead end-to-end technical operations for the Databricks-based data platform in a 24×7 environment.
• Oversee data ingestion, ETL/ELT processes, data quality, and pipeline orchestration.
• Ensure high availability, performance, and security of data platforms.
• Monitor, troubleshoot, and resolve production issues in real-time.
• Collaborate with cross-functional teams including Cloud Infrastructure, DevOps, Data Engineering, and Analytics.
• Optimize Databricks clusters, jobs, and workflows for cost and performance efficiency.
• Implement best practices for CI/CD, version control, and automation.
• Drive incident management, problem management, and root cause analysis (RCA).
• Guide and mentor team members in Databricks, Spark, and Cloud data ecosystem.
• Prepare operational documents, runbooks, and performance reports.
• Work closely with stakeholders to prioritize tasks and ensure SLA compliance.

Required Skills & Qualifications:

• 12–15 years of experience in Data Engineering / Data Platform Operations.
• Strong hands-on experience with Databricks, Apache Spark (PySpark/Scala), and Delta Lake.
• Solid knowledge of Azure Data Services (Azure Data Factory, ADLS, Azure SQL, Synapse, Event Hub, etc.) or AWS equivalents.
• Experience managing 24×7 operations, production support, and incident management.
• Expertise in building, managing, and optimizing ETL/ELT jobs and data pipelines.
• Strong understanding of CI/CD pipelines, DevOps practices, and Git-based version control.
• Good understanding of monitoring tools, logging frameworks, and alerting systems.
• Ability to handle large-scale distributed systems and high-volume data environments.
• Excellent communication, leadership, and stakeholder management skills.

Preferred Skills:

• Experience with Python and SQL for data transformations and automation.
• Familiarity with Databricks REST APIs, job orchestration, and cluster automation.
• Knowledge of ITIL processes (Incident, Problem, Change Management).
• Exposure to on-call rotations and global support models.
• Experience with cost optimization strategies in Databricks and cloud platforms.

Job Type: Full-time

Work Location: In person