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Pushpa Pandey

@pushpapandey

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Senior Data Engineer specializing in cloud data platforms, ETL, and scalable analytics solutions.

United States

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What I'm looking for

I seek roles building cloud-scale data platforms and pipelines, emphasizing data quality, governance, and cross-team collaboration.

I am a Senior Data Engineer with 8+ years building data platforms for analytics, BI, and machine learning across financial services, healthcare, and retail.

I specialize in cloud and big data systems (AWS, Azure, GCP, Databricks, Snowflake) and have hands-on ownership of batch and real-time pipelines, data modeling, and governance.

I have led migrations, designed enterprise data lakes and ETL frameworks, implemented security and governance with Purview/Lake Formation, and automated infrastructure with Terraform and Azure Bicep.

I partner closely with cross-functional teams, mentor junior engineers, and deliver secure, high-quality data solutions that enable analytics, reporting, and ML workflows.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

CVS Health

Oct 2023 - Present (2 years 4 months)

Designed and deployed scalable Azure-based ETL frameworks and a unified Data Lake Gen2 platform, migrating legacy SQL Server workloads to Databricks and enabling near real-time processing for claims and pharmacy data while enforcing enterprise security and governance.

Azure Data Factory Databricks Delta Live Tables Snowflake Pyspark Terraform Azure Synapse Azure Event Hubs Microsoft Purview

Data Engineer

Discover Financial Services

Nov 2021 - Sep 2023 (1 year 10 months)

Built and maintained scalable AWS Glue and Databricks ETL/ELT pipelines processing 2+ TB/day, implemented near real-time Snowflake ingestion and reduced compute costs ~30% through tuning and infrastructure automation.

AWS Glue Databricks Snowflake Pyspark Apache Airflow Kinesis Terraform Great Expectations AWS Lambda

Big Data Engineer

Orion Capital Group

Jun 2018 - Oct 2021 (3 years 4 months)

Designed and operated petabyte-scale Hadoop pipelines and real-time ingestion frameworks, built custom ingestion and transformation tools, and optimized data warehouse performance for large-scale financial transaction analytics.