We are seeking an experienced DFS Tower Lead / L3 Production Support Engineer to provide technical leadership and advanced production support for enterprise data platforms and business-critical data pipelines. The role requires strong expertise in AWS, Databricks, Airflow, Dremio, Python, SQL, and data quality, with a focus on incident management, RCA, platform stability, upgrades, and continuous service improvement.
Required Technical / Functional Skills
- Strong experience with AWS, S3, Athena, and CloudWatch.
- Hands-on experience with Databricks, Dremio, and Apache Airflow.
- Strong programming and troubleshooting skills in Python and SQL.
- Experience with GitHub for source control and deployment support.
- Strong knowledge of metadata, data profiling, schema validation, and data quality checks.
- Experience with regression testing, runtime upgrades, patching, and environment maintenance.
- Strong expertise in production support, incident management, RCA, and permanent corrective actions.
- Good understanding of enterprise data platforms, ETL/ELT pipelines, and downstream data dependencies.
- Strong communication, stakeholder management, and technical leadership skills.
Roles & Responsibilities
- Lead L3 production support for enterprise data platforms and business-critical data pipelines.
- Monitor and support workloads across AWS, Databricks, Dremio, and Airflow environments.
- Troubleshoot complex production incidents and ensure resolution within defined SLAs.
- Perform detailed Root Cause Analysis (RCA) and implement permanent fixes.
- Analyze, debug, and optimize Airflow ETL/ELT workflows.
- Support Databricks clusters, jobs, notebooks, workflows, and runtime configurations.
- Use Python and SQL for troubleshooting, data validation, analysis, and operational activities.
- Monitor platform health and performance using AWS CloudWatch.
- Support data stored in S3 and queried through Athena.
- Perform data profiling, metadata validation, schema validation, and data quality checks.
- Support schema changes, column additions, and data model enhancements while ensuring downstream compatibility.
- Execute regression testing for deployments, platform changes, and infrastructure upgrades.
- Lead/support Databricks runtime upgrades, patching, and environment maintenance.
- Use GitHub for version control, release tracking, and deployment support.
- Collaborate with Data Engineering, Architecture, Business, and Infrastructure teams to resolve issues and improve platform stability.
- Participate in on-call support and critical incident management as required.
- Create and maintain operational runbooks, knowledge articles, and support documentation.
- Drive continuous improvement, automation, operational efficiency, and service stability across the data platform.