Vidushi Verma

Consumer Digital Data Taxonomy: Building a shared business-taxonomy layer across UHG and Optum data domains, giving engineers and analysts a consistent way to discover, understand, and access data. Standardizing reusable datasets and metadata to reduce duplicate effort and accelerate delivery through AI-assisted workflows.

Senior Data Engineer at UnitedHealth Group – Optum (2026-07 – Present)

• Consumer Digital Data Taxonomy: Building a shared business-taxonomy layer across UHG and Optum data domains, giving engineers and analysts a consistent way to discover, understand, and access data. Standardizing reusable datasets and metadata to reduce duplicate effort and accelerate delivery through AI-assisted workflows.

Data Engineer Intern at Qualcomm (2026-05 – 2026-07)

• Agentic AI Platform: Building DEAN (Data Engineering Agentic Network) – a multi-agent LLM application (FastAPI + LangGraph + Databricks) that automates enterprise data pipelines end-to-end using LLM agents for schema modeling, code generation, data quality validation, and QA.

Senior Data Engineer at UnitedHealth Group – Optum (2021 – 2024)

• Large-Scale Data Pipelines: Architected 50+ production distributed pipelines processing TB-scale healthcare data in real time using Scala, Spark, Kafka, Hadoop/HDFS, and Hive; built a reusable ingestion framework adopted by 5+ teams, cutting latency 80% and achieving 99.9% uptime through zero-disruption cloud migration; delivered trusted datasets for downstream analytics and business metrics.
• Analytics Data Modeling: Built and maintained dbt transformation models in Snowflake for canonical analytics datasets; defined incremental materializations, source freshness checks, schema tests, and documentation to improve data integrity and make metrics understandable to downstream teams.
• Database & Query Performance: Optimized Snowflake and cloud SQL query execution (60% latency reduction) via query plan analysis, partitioning, indexing, and predicate pushdown; designed columnar storage schemas for analytical workloads and reporting.
• Cloud Migration & Infrastructure: Migrated on-premise Hadoop/HDFS and Hive data pipelines to Azure (ADF, ADLS Gen2, Databricks) with zero downtime; automated pipeline orchestration using Airflow, reducing manual intervention and achieving end-to-end observability with data freshness and reliability metrics across 50+ jobs; applied validation, access controls, and audit-ready checks for sensitive healthcare data.
• Stakeholder Analytics: Partnered with Product, Engineering, and go-to-market stakeholders to translate reporting needs into shared datasets and KPI definitions; built Hex dashboards and self-serve reporting views that supported recurring performance reviews and data-driven decisions.

Software Engineer at Unilever (2019-06 – 2021-11)

• B2C & B2B Data Pipelines: Built and maintained database-backed data pipelines for B2C online ordering platforms (HUL salesmen) and the Shikhar B2B retailer platform – integrated multiple data sources using SQL, stored procedures, ETL, and reverse ETL workflows; published operational datasets and metrics to support high-volume retailer and salesman transaction flows with improved throughput and data integrity.
• Reporting & Self-Serve Analytics: Worked with business teams to define operational KPIs and reporting requirements; created reusable data views and dashboards that enabled sales and retail stakeholders to monitor performance without recurring engineering support.

M.S. in Data Intelligence – San Jose State University (2025 – 2026)

B.Tech in Electronics Engineering – APJ Abdul Kalam Technical University (2014 – 2018)