Ajay Kumar

About Ajay Kumar

I’m a data professional with 5+ years of experience building cloud-based data pipelines and analytics layers using Python and SQL. I enjoy taking scattered data from different systems and turning it into clean, reliable datasets that teams can trust for reporting and decision-making.I’ve worked across the full lifecycle, ingesting data from APIs, files, operational systems, and event/IoT sources, then transforming and modeling it for analytics and dashboards. I’m comfortable working in production environments: debugging pipeline failures, improving performance, and making workflows stable enough that business teams don’t have to worry about refreshes and broken reports.I’ve completed my Master’s in Data Science, which strengthened my approach to data modeling, analytics use cases, and building quality into pipelines from the start.What I typically work on:Python + advanced SQL for transformations, automation, and data prepETL/ELT pipelines and curated datasets for reporting/analyticsData modeling for warehouse-ready tables (facts/dimensions, reporting layers)Orchestration and automation (scheduling, retries, backfills, dependencies)Data quality and monitoring (profiling, reconciliation checks, alerts)Dashboards and KPI reporting in Power BI/TableauExposure to streaming/event-driven patterns (Kafka/Spark concepts) for low-latency needsRight now, I’m actively exploring Data Engineer / Data Analyst / Data Scientist/ BI-focused roles where I can build scalable pipelines, improve trust in data, and support faster decision-making. If you’re hiring for someone strong in Python, SQL, ETL, cloud data, and dashboards, feel free to message me.

Experience

1. Data Engineer

   Humana

   Jan 2024 — Present · US

   Architected and maintained hybrid cloud data pipelines across AWS (S3, Glue) and Azure (ADF, Databricks), integrating healthcare data from 15+ source systems for enterprise analytics and reporting.• Built FHIR and HL7 data ingestion pipelines on AWS S3 and Glue with schema validation and comprehensive error handling, ensuring reliable ingestion across multiple clinical data formats.• Optimized PySpark workloads using dynamic partitioning, broadcast joins, and caching, cutting ETL runtime by 40% and reducing computing costs by 25%.• Designed and deployed real-time streaming pipelines using Kafka and Spark Structured Streaming, enabling sub-second event processing for clinical data feeds.• Implemented Delta Lake CDC (Change Data Capture) patterns in Azure Databricks, reducing incremental load times by 60% compared to full-refresh batch jobs.• Orchestrated production ADF pipelines with SLA monitoring, dependency handling, and automated alerting, maintaining consistent data freshness for downstream BI consumers.• Developed dbt models in Snowflake using incremental and snapshot materialization strategies, deploying tested transformation logic via GitHub Actions CI/CD for faster, reliable analyst workflows.• Established HIPAA-compliant data governance using column-level encryption, IAM-based role controls, and automated Python/SQL data quality checks, reducing data incidents by 30%.

Education

• Gandhi Institute of Technology and Management (GITAM)

  Bachelor of Technology, Computer Engineering

• University of Houston-Clear Lake

  Master of Science, Data Science

• Vignan High School

  10th

  2014 — 2015

• University of Houston-Clear Lake

  Master's degree, Data Science

• GITAM Deemed University

  Bachelor of Technology, Computer Science

  2017 — 2021

• Narayana Junior college, Hyderabad

  Mathematics Physics Chemistry (MPC)

  2015 — 2017