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Prerit Mahajan

@preritmahajan1

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Senior Data Engineer building scalable ETL/ELT and lakehouse architectures that power analytics and AI/ML pipelines.

United States

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What I'm looking for

I’m looking for a production-focused data engineering role where I can design resilient ETL/ELT, strengthen data quality monitoring, and partner with data scientists to deliver AI/ML-ready datasets at scale.

I’m a Senior Data Engineer with 10+ years designing and maintaining scalable ETL/ELT pipelines, data models, and lakehouse/data warehouse architectures across AWS, Azure, and GCP. I turn raw, semi-structured data into reliable, structured formats that directly support analytics and AI/ML workflows.

At Oasys International, I architected enterprise pipelines using Python, PySpark, NumPy, and SQL—reducing analysis turnaround by 30% and cutting 8-hour processing runs to under 6 hours. I also built Medallion Architecture models for 500,000+ record datasets and deployed data quality monitoring aligned with Great Expectations across 5+ concurrent workstreams.

I’ve driven production impact through REST API integrations, CI/CD-driven automation (reducing manual operations by 70%), and cross-team collaboration—improving congestion prediction model accuracy by 25%. Earlier roles include building ELT/ETL systems for 5M+ records/month with 99.9% uptime, and delivering high-performance ML and data services at Nike supporting 50M+ users during global launches.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

Oasys International, LLC

Apr 2021 - Jan 2026 (4 years 9 months)

Architected and maintained enterprise ETL/ELT pipelines that reduced analysis turnaround by 30% and cut 8-hour runs to under 6 hours. Built Medallion Architecture data models and Great Expectations-aligned data quality monitoring, improving data integrity across 5+ concurrent research workstreams.

Python Pyspark SQL ETL Medallion Architecture Delta Lake Great Expectations Apache Airflow Terraform Docker

Data Engineer

The Judge Group

May 2017 - Mar 2021 (3 years 10 months)

Designed and maintained ELT/ETL pipelines across 6 integrations for a top-10 U.S. health payor, processing 5M+ member/claims records per month while reducing processing delays by 50% and increasing throughput by 40%. Implemented data models, validation rules, and batch workflows with Airflow to reduce data quality incidents by 60% and cut manual operations by 80%, saving 20+ hours/week.

ETL SQL Python Apache Airflow Data Modeling Data Validation PostgreSQL MySQL Data Quality Batch Processing

Data Scientist

Nike

Sep 2013 - Apr 2017 (3 years 7 months)

Built high-performance Python and Java data services on the SNKRS platform, sustaining 2M+ simultaneous requests with sub-100ms latency during global launch events. Developed an ML-based anti-bot detection pipeline that reduced automated abuse by 65% and protected $10M+ in annual GMV.

Python Java Machine Learning Data Pipelines Anti Bot Modeling Redis AWS GCP Performance Optimization

SQL Developer

Google

Jan 2012 - Aug 2013 (1 year 7 months)

Developed SQL and C++ components for Mesa to support analytics pipelines processing 10B+ rows/day across petabyte-scale, multi-datacenter environments. Contributed to MapReduce ETL optimizations and improved cross-datacenter reliability from 97.2% to 99.4% through consistency and replication mechanisms.

SQL C++MapReduce Distributed Systems ETL Replication Cross Datacenter Reliability Performance Tuning