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Prashanna pandit

@prashannapandit

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Senior data engineer modernizing enterprise lakehouses with governance-first pipelines and GenAI-ready data products.

United States

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What I'm looking for

I’m looking for a role where I can modernize cloud data platforms with lakehouse architectures, governance-first pipelines, and reliable batch/streaming foundations—while building GenAI-ready data products that support analytics and regulated healthcare workloads.

I’m a Senior Data Engineer with 7+ years of experience designing and modernizing enterprise data platforms across healthcare and financial services on GCP, AWS, and Azure. I lead cloud migration and data platform architecture by moving legacy Synapse and ADLS workloads into modern Databricks Lakehouse architectures, and I’ve re-engineered Snowflake and BigQuery environments to reduce compute spend and improve query performance—delivering over $800K in annual savings through warehouse optimization and cloud FinOps.

I build modular, tested transformation layers with dbt and deliver production AI/GenAI data pipelines, including RAG solutions spanning ingestion, chunking, embeddings, vector search integration, and prompt orchestration. In regulated environments, I take a governance-first approach for HL7/FHIR pipelines with schema evolution controls, audit-ready lineage, data contracts, and automated quality validation—partnering with Data Science, Security, Compliance, DevOps, and Architecture teams to ship secure, fault-tolerant, business-critical data products.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

CVS Health

Jun 2024 - Present (2 years 1 month)

Designed and built scalable data pipelines and a lakehouse architecture on AWS for healthcare claims and EHR processing. Re-engineered warehouse platforms and delivered governed transformation and AI/GenAI RAG pipelines, improving reliability, performance, and cost.

Data Engineer

Allstate Corp.

Oct 2022 - May 2024 (1 year 7 months)

Built and maintained scalable ETL/ELT pipelines on Azure using ADF, ADLS Gen2, Databricks, and Synapse for claims, policy, and customer data. Implemented real-time ingestion, modular dbt transformations, governance/security controls, and automated CI/CD to improve reliability and deployment efficiency.

Data Engineer

Northwestern Mutual

Aug 2019 - Sep 2022 (3 years 1 month)

Developed scalable data pipelines on Google Cloud for risk, claims, policyholder, and underwriting workloads. Built batch and near real-time ETL with BigQuery curation, dbt-based transformations, automated data quality checks, and governance controls for regulated data.