Sankar Sundaram

10+ years as a Data/AI engineer and Cloud/AI solutions architect designing and deploying enterprise-scale data platforms, with recent hands-on focus on AI/LLM engineering and agentic workflows — building large-scale ELT/ETL and lakehouse platforms on Databricks, API ingestion, Delta Sharing, and orchestration across Airflow, dbt, and Python. Depth in enterprise data warehousing: dimensional modeling, T-SQL, stored procedures, and high-availability SQL Server, with a proven record migrating legacy on-prem data warehouses to modern Delta Lake and optimizing pipeline reliability to 99.999% SLA. Adept at driving CI/CD initiatives and collaborating across teams to deliver secure, scalable, AI-powered solutions — including LLM-integrated agents and MCP-based tool orchestration built directly into the delivery pipeline.

603-930-7755 [email protected] Jacksonville, FL LinkedIn ↗ GitHub ↗
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10+
Years in data engineering & cloud architecture
1.8B+
Rows ingested in a single retail sales pipeline
99.999%
SLA reliability across 30+ production pipelines
180+
ERP source tables migrated to Delta Lake

Core expertise

Cloud & Lakehouse Platforms

  • Azure Databricks & Delta Lake
  • Google BigQuery & GCP
  • Azure Data Factory, Synapse & Microsoft Fabric
  • Azure SQL DB & SQL Server

Orchestration & Transformation

  • Apache Airflow (Python DAGs)
  • dbt (Data Build Tool)
  • Spark SQL & PySpark
  • Kafka & Spark Structured Streaming
  • Databricks Asset Bundles

Data Modeling & SQL Engineering

  • T-SQL, Stored Procs, Functions & Triggers
  • Performance Tuning & Query Optimization
  • Data Warehousing — Dimensional, Medallion & Data Vault Modeling
  • Unity Catalog & Governance (RBAC, Lineage)

Delivery & Platform Ops

  • CI/CD — Azure DevOps, GitHub, Bitbucket
  • Terraform, Docker & Kubernetes
  • Power BI, Tableau, SSRS & SSIS
  • Agile / Scrum & SDLC

Agentic Engineering & GenAI

  • Claude Code, Cursor & Codex
  • MCP (Model Context Protocol)
  • Agent Frameworks & Tool Orchestration
  • Python Development
  • Generative AI & LLM Integration

Experience

Sr. Data Engineer / Architect (Azure) · Beaver Street Fisheries
Jacksonville, FL
Apr 2025 – Present
  • Own end-to-end delivery of ERP migration, pricing analytics, retail sales integration, and product information initiatives on an Azure Databricks Lakehouse (medallion / Delta Lake) architecture.
  • Led migration of 180+ ERP source tables to Delta Lake, building Python DAGs orchestrated in Apache Airflow, replacing legacy on-prem batch processing with zero schema-change handling errors.
  • Designed 30+ production Airflow pipelines covering 180+ tables, raising pipeline reliability to 99.999% SLA.
  • Engineered ingestion and modeling of Walmart retail sales data at 1.8B+ row scale, tuning partitioning, Z-ordering, and liquid clustering, and leveraging the Photon accelerator to speed up Spark query execution for 10× faster analytical queries.
  • Authored and tuned T-SQL stored procedures, functions, and triggers in Azure SQL DB for ERP validation logic, applying performance tuning and query optimization.
  • Configured Always On Availability Groups, replication, and clustering (WSFC) for Azure SQL DB high availability and disaster recovery.
  • Implemented Databricks Asset Bundles (DABs) for CI/CD-deployed, versioned pipeline releases; enabled cross-org data sharing via Delta Sharing.
  • Extended the Databricks lakehouse into Microsoft Fabric / OneLake to support enterprise reporting workflows for downstream BI consumers.
  • Mentored engineering management and the broader team on the lakehouse architecture end-to-end — from design decisions through production implementation — building shared technical ownership across the organization.
  • Built and deployed an AI code-review agent using Claude Code, applying MCP (Model Context Protocol) tool orchestration and agentic engineering to automate pull-request review directly in the CI/CD pipeline.
Cloud Data Architect / Engineer (GCP) · Venus
Jacksonville, FL
Jun 2023 – Apr 2025
  • Migrated an on-prem SQL Server enterprise data warehouse to Google BigQuery, reducing report-refresh latency from 20 minutes to 2 minutes.
  • Migrated legacy T-SQL stored procedures, functions, and triggers into BigQuery SQL and Databricks, applying database design and performance-tuning best practices.
  • Developed dbt transformation pipelines structuring raw data into curated gold-layer models for self-service BI.
  • Built Cloud Run services ingesting API data into BigQuery and Snowflake; established DevOps best practices in Azure DevOps.
  • Applied agentic engineering and Python-based GenAI/LLM integration to prototype workflow-automation agents, evaluating and using multiple AI coding tools and LLMs — including Claude Code, Cursor, and Codex — and comparing agent frameworks and tool-orchestration patterns for practical business use cases.
Data Engineer (Azure) · Microsoft Inc.
Redmond, WA
Nov 2021 – Jun 2023
  • Designed large-scale big-data pipelines for sustainability analytics on Azure Databricks and ADF/Synapse, improving reliability to 99.999% SLA.
  • Built ADF/Databricks pipelines across ADLS Gen2, Azure SQL, Event Hub, and Logic Apps; implemented governance and lineage with Microsoft Purview.
  • Delivered interactive Power BI and Tableau dashboards using PySpark, Databricks notebooks, and Spark SQL.
Technical Lead / Full Stack Data Engineer · Pfizer Inc.
Groton, CT
Dec 2020 – Nov 2021
  • Delivered big-data migration and API integrations on GKE, Cloud Dataflow, Cloud Run, and Cloud SQL; built an analytics platform on Snowflake and SnowSQL.
  • Ingested data via AWS Glue, S3, and Lambda; ran CI/CD with Kubernetes, Docker, Jenkins, and Bitbucket.
  • Built API integrations with Veeva Vault CRM and Veeva Link to ingest field-sales and medical-affairs data into the Snowflake analytics platform for commercial reporting.
  • Supported regulatory and quality data flows by integrating pipelines with Veeva RIM and Veeva QMS, ensuring traceable, audit-ready data for compliance reporting.
  • Led Veeva LIMS implementation end-to-end — requirements, workflow design, configuration, integration, and testing — partnering with Lab, Quality, IT, and Business Process Owners through UAT and go-live.
  • Applied risk-based CSV/CSA and GxP principles across Veeva LIMS configuration and documentation, aligning with 21 CFR Part 11, EU Annex 11, GAMP 5, and ALCOA+.
Solutions Architect (Azure) · Cirrus Aircraft / Daikin
Minneapolis, MN
Aug 2019 – Nov 2020
  • Built ETL/ELT and ML pipelines using ADF, Azure Databricks, Spark, and Python for R&D and IoT/sensor streaming data.
  • Designed star/snowflake schema models in Snowflake; automated IaC deployment with Terraform and Azure DevOps.

Education & certifications

Master of Science in Cyber Security (MSCS)

EC-Council University, Albuquerque, NM · GPA 3.80 / 4.0

Certifications

  • Google Certified Professional Cloud Architect
  • Microsoft Certified: Azure AI Engineer Associate
  • Databricks Lakehouse Fundamentals
  • Certified Gen AI for Data Engineers
  • Google Cloud Digital Leader

Earlier experience

Data Analytics Consultant
2017 – 2019
Wells Fargo & US Bank, MN

Migrated SAS reporting to SQL/Azure Data Lake; built ETL (SSIS, ADF) and Power BI/Tableau analytics.

Technical Lead – IAM
2016 – 2017
Biogen, MA

Led enterprise systems integration; built Azure Data Lake, Informatica, and Oracle PL/SQL data ingestion.

Delivery Lead
2009 – 2016
Pfizer Inc., CT

Delivered BI/DW solutions (Informatica, OWB, Tableau, SAS) and MDM for life-sciences applications, integrating feeds from Veeva Vault (QualityDocs, eTMF).