Résumé

Data & AI Engineer

I build scalable data platforms and AI infrastructure for trusted enterprise workflows.

Python, SQL, Spark, Beam, Kafka, Airflow, Iceberg, BigQuery, Rust, TypeScript, RAG, vector search, and agentic AI systems.

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Snapshot

Enterprise data systems, now focused on trusted AI workflows.

Experience
4+ years
Focus
Data platforms · AI systems
Current
Enterprise modernization
  • Data platforms
  • Streaming pipelines
  • Cloud modernization
  • ML systems
  • RAG workflows
  • Governed AI

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