M Faizan

Data Engineer

Cigna • Full time

Aug 2019 - Present • 6 yrs 11 mos

• Designed, developed, and maintained distributed data pipelines using PySpark and Hadoop to process multi-terabyte healthcare datasets efficiently. • Built and optimized ETL workflows in Databricks, integrating data from Teradata, S3, and API-based sources for analytics and reporting teams. • Wrote complex Hive and Spark SQL queries to transform raw data into standardized, high-quality datasets used for predictive models and dashboards. • Implemented data quality testing frameworks to validate pipeline outputs and ensure compliance with regulatory standards (HIPAA). • Spearheaded a platform modernization initiative migrating legacy Hadoop workloads to Databricks and AWS, improving processing times by 40%. • Collaborated with cross-functional Business and Application teams to define data models, performance KPIs, and governance standards. • Managed and mentored a team of onshore and offshore developers, overseeing code reviews, sprint planning, and workload prioritization. • Automated job orchestration and monitoring through Airflow and AWS Glue, reducing manual intervention by 60%. • Supported infrastructure upgrades, capacity planning, and performance tuning across multiple data environments. • Key Achievements: • Delivered 20+ production-grade Spark pipelines with 99.9% uptime. • Reduced ETL processing time from 6 hours to 2.5 hours via optimized Spark partitioning and caching. • Recognized by leadership for outstanding collaboration and system modernization contributions (2024).