Data & AI Engineer

Experience

1. 00

   Data Engineer

   Wells Fargo · via Capgemini America Inc.

   Oct 2025 – Present · Charlotte, NC

   Leading GenAI-assisted modernization, lakehouse architecture, and event-driven ingestion for regulated financial data.

   • 900+
     Java modules migrated
   • 35+
     financial datasets
   • 20+ yrs
     reporting context

   • Led a GenAI-assisted modernization initiative using GitHub Copilot to migrate 900+ legacy Java modules into Spark and Apache Beam pipelines in roughly 7 months versus a 2+ year manual rewrite estimate.
   • Architected an Apache Iceberg + BigQuery lakehouse for an on-prem-to-GCP migration POC, onboarding 35+ financial datasets with SAR/CSAR compliance considerations.
   • Built event-driven ingestion on GCS, Airflow, and Dataflow with schema enforcement, DQ checks, curated lakehouse outputs, and a BigQuery semantic layer over 20+ years of financial data.

   • GCP
   • GitHub Copilot
   • Apache Beam
   • Spark
   • Airflow
   • Dataflow
   • BigQuery
   • Apache Iceberg
2. 01

   Data Specialist

   University of Maryland

   Sep 2023 – May 2025 · College Park, MD

   Built high-throughput analytics and AI systems for academic operations and research.

   • 20M/day
     ELMS events → BQ
   • 6h→45m
     119-table CDC
   • 5d→2d
     survey RAG review

   • Engineered a Pub/Sub + Dataflow streaming pipeline ingesting 20M+ daily ELMS events into BigQuery for real-time Superset dashboards tracking 15 KPIs across 230 academic programs.
   • Overhauled 119 Redshift ingestion workflows in Python, SQL, and AWS with CDC and validation, cutting runtime from 6 hours to 45 minutes.
   • Prepared an LLM-powered RAG POC over 100K+ open-ended survey responses using Python, LangChain, and Elasticsearch, reducing qualitative review effort by 60%.

   • BigQuery
   • Pub/Sub
   • Dataflow
   • LangChain
   • Elasticsearch
   • Python
3. 02

   Senior Software Engineer. Data Platform

   Tiger Analytics

   Jul 2021 – Jul 2023 · Chennai, India

   Led delivery of a self-serve data fabric used by Fortune 500 clients.

   • 6
     enterprise clients
   • 75%
     onboarding time cut
   • 85+
     analysts + ML engineers

   • Led a 7-engineer team building a self-serve AWS data platform that enabled data mesh adoption across 6 enterprise clients.
   • Designed an Apache Iceberg lakehouse on S3 with Glue Catalog, schema evolution, ACID transactions, and time-travel queries for reproducible ML training datasets and historical analytics.
   • Developed Airbyte/Airflow batch and streaming ingestion with CDC, encryption, Macie PII detection, and a Spark + Deequ DQ framework with 30+ rules, reducing onboarding time by 75% and blocking 85% of bad data before downstream ML.
   • Shipped FastAPI microservices on Kubernetes exposing ELT orchestration as self-serve REST APIs for 85+ analysts and ML engineers.

   • AWS
   • Spark
   • Airflow
   • Airbyte
   • FastAPI
   • Kubernetes
   • Apache Iceberg
   • Deequ
4. 03

   Intern & Software Engineer

   Xenonstack Pvt. Limited

   Jan 2019 – Nov 2019 · Chandigarh, India

   Built the data engineering foundation for realtime analytics and MLOps workflows.

   • 10GB/day
     45 IoT sites
   • 15min
     forecast freshness
   • 33%
     MLOps iteration ↑

   • Delivered Spark + Kafka pipelines processing 10GB/day of IoT telemetry from 45 geo-distributed sites into a medallion Delta Lake.
   • Enabled incremental forecasting pipelines with 15-minute prediction freshness.
   • Improved ML iteration speed by 33% through MLflow integration.

   • Databricks
   • Spark
   • Kafka
   • Delta Lake
   • MLflow

Education

1. Master of Information Management

   University of Maryland. College Park

   Aug 2023 – May 2025 · College Park, MD

   • Graduate assistantship as Data Specialist. Built analytics + AI systems across 230 academic programs.
   • Coursework: distributed systems, retrieval, applied ML, data governance.

2. B.E. Information Technology

   Panjab University, Chandigarh

   2015 – 2019 · India