Professional Experience
- Designed and implemented scalable data pipelines using Python, Spark, and PySpark.
- Led data migrations with zero data loss to modern platforms.
- Optimized ETL workflows for performance and scalability.
- Built fraud detection models using H2O.ai for production use.
- Integrated validation checks for enterprise data quality.
- Automated batch processing using Oozie, Airflow, and CA7.
- Collaborated cross-functionally for business insights.
- Mentored junior engineers and promoted code best practices.
- Deployed real-time analytics using Azure and AWS.
- Implemented CI/CD pipelines using Azure DevOps & Docker.
- Published 19+ research papers across AI, ML, and data engineering domains.
- Reviewed 30+ publications as peer reviewer and editorial board member.
- Keynote speaker at IC-DEST’23 on AI in cybersecurity and finance.
- Contributed to open-source PySpark/ML templates & utilities.
- Featured in media outlets like The Hans India and TechBullion.
Technical Skills
- Big Data: Hadoop, Spark, Hive, Pig, Kafka, Sqoop, Oozie, Airflow
- Languages: Python, Scala, SQL, Unix Shell
- Cloud: Azure, AWS (EMR, S3, Redshift)
- ML Frameworks: H2O.ai, Scikit-learn, TensorFlow, Keras
- Storage: Azure Data Lake, MongoDB, PostgreSQL, MySQL
- CI/CD: Azure DevOps, Jenkins, Docker, Git, Kubernetes
Awards & Recognition
- ISSN International Research Award: Groundbreaking AI research
- TITAN Business Award (Silver): IT Future Leader of the Year
- Global Recognition Award 2024: Leadership in Data Engineering
- NEW RAINS Research Excellence Award: Advancing AI and Tech Research
Education
- Masters of Science in Computer Science – Purdue University Northwest
- Bachelor’s of Technology in Electronics and Communications Engineering – KL University