Mukesh Rajmohan

About

Data engineer with experience across healthcare and geospatial risk systems, owning end-to-end pipelines from ingestion through serving on AWS/Azure stacks. Built HIPAA-compliant data quality gates and CDC for millions of daily claims, and also delivered a real-time wildfire risk platform with 20-minute refresh cycles and a 60% data accuracy lift. Strong in streaming (Kafka), Spark performance tuning, and production-grade orchestration/CI/CD (Airflow, Docker, Jenkins, GitHub Actions, Terraform).

Key Strengths

• Owned end-to-end ELT pipeline ingesting millions of daily healthcare claims/eligibility records
• Built automated Python/SQL data quality gates (schema enforcement, distributional checks) and CDC to prevent corrupted data reaching serving layer
• Implemented HIPAA-compliant PII tagging and compliance-oriented data controls
• Improved ingestion efficiency by 40% and accelerated feature delivery by 25% via Airflow + CI/CD (Jenkins/Docker)
• Designed real-time geospatial ingestion with 20-minute refresh cycles and validation correcting geometry/temporal outliers (60% accuracy increase)
• Hardened external API ingestion with monitoring, sensors, retries (exponential backoff), rate limiting, and fail-fast schema change detection
• Shipped real-time risk platform using Kafka + PySpark on Azure Synapse; reduced query latency by 50%
• Performance debugging using Azure Monitor/Spark UI; optimized joins and applied Delta Lake Z-ordering
• Established modular, testable transformations with dbt tests and documented data contracts for downstream consumers

Experience

Education

Skills

Languages

Publications

1 publication

Memberships

• ACM