Somdutta Sanyal

About Somdutta Sanyal

Data Engineer and Data Architect with 20+ years of experience building large-scale data pipelines, distributed data systems, and enterprise data warehouse architectures across legal tech, eCommerce, and social media domains.Currently embedded with Meta\'s Legal Technology Data Engineering team, where I lead the technical direction for data engineering initiatives and drive AI adoption using Claude Sonnet (LLM) via Meta\'s internal AI interface. I build pipelines, design schemas, and create tooling — and I do a significant portion of that work using AI-assisted engineering:Co-architected an AI-powered on-call automation agent that auto-resolves 50% of all incident tasks, replacing manual coding with peer-review-ready AI-generated codeBuilt an Ops Health Dashboard monitoring ~600 pipelines and ~1,200 Hive tables in real time, achieving a 10x reduction in on-call triage timeDesigned an AI Adaptability Dashboard that tracks LLM tool adoption across the engineering team, giving leadership visibility into AI maturity and productivity impactBeyond Meta, my background spans StubHub (eBay) where I served as Data Architect for nearly six years — leading cloud migration from on-prem Oracle to GCP (BigQuery, BigTable, Spanner), driving GDPR compliance, building a data security classification portal, and governing the enterprise data governance group across 8+ scrum teams.Domain expertise: eCommerce · Social Media · Legal Technology · Business Intelligence & Reporting · Data Warehousing · Catalog ManagementCore technical strengths: SQL · Python · PL/SQL · Presto · Hive · HBase · Apache Airflow · GCP (BigQuery, BigTable, Dataflow, DLP API) · Informatica · Oracle Warehouse Builder · ERStudio · ERWIN · Tableau · Dimensional & OLTP Modeling · Data Governance · GDPR / PCI / PII / SOXCurrently pursuing certifications in: Generative AI with Large Language Models (DeepLearning.AI, Feb 2026) · Generative AI for Everyone (DeepLearning.AI, Jan 2026)I\'m passionate about the intersection of data engineering and AI — specifically how LLMs can be applied to automate, accelerate, and improve the quality of data infrastructure work. Always open to conversations about data architecture, AI-assisted engineering, and building high-impact data teams.

Experience

1. Senior Data Engineer

   Meta

   May 2020 — Present · Fremont, CA, US

   Part of Meta\'s Legal Technology Data Engineering team, delivering data infrastructure across Copyright, Legal Matter Management, Legal Analytics, Machine Learning, and Safety & Integrity.o Leveraged Claude Sonnet (LLM) via Meta\'s internal AI interface to streamline pipeline code generation, schema design, and technical documentation. Co-developed an AI-powered On-Call Automation Agent that auto-diagnoses pipeline failures, generates peer-review-ready code, and auto-resolves 50% of on-call incidents.o Designed an Ops Health Dashboard covering ~600 Dataswarm pipelines and ~1,200 Hive tables, replacing fragmented manual monitoring and achieving a 10x reduction in triage time. Built an AI Adoptability Dashboard giving leadership visibility into LLM tool adoption rates and productivity trends.o Designed data models for the Legal Data Mart across AML, Copyright & Infringement, and Legal Matter Management domains. Built and maintained ETL pipelines using Meta\'s Dataswarm framework (Apache Airflow equivalent) with full lifecycle ownership: design, testing, peer review, CI/CD deployment, and enhancement. Redesigned underperforming pipelines to resolve throughput and latency bottlenecks.o Architected a Data Protection Framework for payment data retention — assigning retention policies by legal classification, monitoring for missing tables/partitions, auto-generating JIRA alerts, and visualizing impact metrics via Tableau.o Partnered with stakeholders across Compliance, Legal Matter Management, Copyright, and Legal Analytics to translate requirements into scalable data models supporting executive dashboards. Authored Presto SQL for pipeline execution and ad hoc analytics. Worked across multiple agile scrum teams, converting business requirements into epics, stories, and technical specification documents.

Education

• ST. Thomas' College of Engineering and Technology

  Bachelor's degree, Electrical, Electronics and Communications Engineering

  2001 — 2005

Skills

• Informatica
• Business Intelligence
• Data Architecture
• Business Objects
• Requirements Gathering
• Oracle
• Requirements Analysis
• Extract, Transform, Load (Etl)
• Database Design
• Data Warehouse Architecture
• Etl
• Data Quality
• Data Analysis
• Erwin
• Hbase
• Dimensional Modeling
• Sql
• Visio
• Erstudio
• Tableau
• Pl/Sql
• Sharepoint
• Agile Methodologies
• E-Commerce
• Databases
• Relational Databases
• Unix
• Data Modeling
• Oracle Warehouse Builder
• Business Analysis
• Data Warehousing
• Business Requirements
• Data Governance