sagar das✳ENGINEER BY TRADE.
CURIOUS BY DEFAULT.

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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Experience

  1. 00

    Senior Data Engineer

    Quantiphi

    Aug 2026 – Present · Marlborough, MA

    Building scalable batch and streaming data platforms for analytics and AI, with a focus on healthcare data interoperability.

    • Designing and building scalable ETL/ELT pipelines and batch plus real-time processing systems, tuned for performance, scalability, and cost efficiency across large structured and semi-structured datasets.
    • Building and maintaining data integration workflows across heterogeneous source systems, with quality, integrity, and reliability controls spanning the full data lifecycle.
    • Designing data models that support downstream analytics and AI use cases, translating stakeholder requirements into technical design.
    • Supporting healthcare data ingestion and transformation against interoperability standards, with CI/CD, testing, and pipeline monitoring built into delivery.
    • 01

      Data Engineer

      Wells Fargo · via Capgemini America Inc.

      Oct 2025 – Aug 2026 · 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
    • 02

      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
    • 03

      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

    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