Open to opportunities

Shiva Sah

@shivasah

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Experienced Data Engineer with a passion for scalable data solutions.

United States

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What I'm looking for

I seek a role that fosters innovation and collaboration, focusing on data-driven solutions.

I am an experienced Data Engineer with about 7 years of expertise in building scalable data platforms and ETL pipelines across AWS, Azure, and GCP. My proficiency in technologies such as Spark, Snowflake, and Databricks allows me to deliver high-performance data solutions that drive analytics and machine learning readiness. I thrive in Agile environments and excel at collaborating cross-functionally to meet business objectives.

At Pfizer, I led a global initiative to modernize clinical and manufacturing analytics by implementing a production-grade lakehouse platform. This project not only streamlined data access across teams but also supported regulatory submissions and real-time analytics. My commitment to data quality and governance has resulted in significant improvements in operational efficiency and compliance across various organizations, including Wells Fargo and Johnson & Johnson.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

Pfizer

Sep 2023 - Present (2 years)

Led Pfizer's global initiative to modernize clinical and manufacturing analytics by delivering a production-grade lakehouse platform integrating genomics, assay, batch, and safety data. This unified foundation supports ML workloads, regulatory submissions, and GxP-compliant real-time analytics across vaccine and oncology programs. Spearheaded the design and implementation of a Medallion-layer lake

AWS Snowflake Databricks Apache Flink Airflow DBT Great Expectations Sagemaker MLFlow OpenTelemetry Power BI Looker GitHub Actions)SQL Python

Senior Data Engineer

Wells Fargo

Jan 2021 - Present (4 years 8 months)

Led cloud transformation initiatives across Wells Fargo's retail and commercial banking lines by designing and scaling a unified financial data platform for real-time fraud detection, regulatory compliance (SOX, CCAR), customer insights, and credit risk analytics across Azure and GCP. Architected scalable ETL pipelines using Azure Data Factory and Databricks (PySpark) to process high-volume credit

Azure Data Factory Databricks Pyspark Azure Event Hubs Apache Kafka Snowflake BigQuery Vertex AI Apache Airflow DBT Great Expectations Terraform Power BI Looker GitHub

Data Engineer

Johnson & Johnson

Sep 2018 - Present (7 years)

Built a cloud-native data platform to integrate Medicare, Medicaid, and clinical datasets, enabling real-time analytics, ML workflows, and regulatory compliance across J&J's pharma and med-tech units using AWS, Azure, Spark, Kafka, and Snowflake. Designed and optimized ETL pipelines using PySpark, processing large-scale healthcare datasets from Medicare, Medicaid, and commercial lines to support a

Apache Spark Scala Pyspark Python Hadoop AWS Azure Docker Kubernetes Snowpipe Snowflake Kafka Terraform DBT Tableau Power BI SQL Apache Airflow GitHub Jira Agile

Education

Degrees, certifications, and relevant coursework

Kalamazoo College

Bachelor's, Computer Science & Business and Economics

Studied Computer Science and Business and Economics, gaining foundational knowledge in both technical and economic principles. Developed skills in problem-solving, data analysis, and business strategy.