Open to opportunities

Thomas Fields

@thomasfields1

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Senior Data Engineer with 8+ years of experience in data platforms.

United States

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What I'm looking for

I am looking for a role that fosters innovation and collaboration, where I can leverage my data engineering skills to drive impactful solutions and contribute to team success.

I am a Senior Data Engineer with over 8 years of experience in designing scalable, reliable, and maintainable data platforms across various domains. Currently, I work at FedEx, where I have designed and deployed scalable data pipelines on Azure Databricks, leveraging Spark to process multi-terabyte delivery scan logs and real-time route telemetry for our global logistics insights platform.

Previously, at Flatiron Health, I built and maintained dbt models on Redshift to structure patient, encounter, and treatment data for oncology research. My expertise includes developing Spark-based batch pipelines, managing DAGs in Apache Airflow, and architecting automated, HIPAA-compliant ETL pipelines. I am passionate about collaborating with cross-functional teams to enhance data quality and system performance.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

FedEx

Oct 2022 - Present (2 years 10 months)

Designed and deployed scalable data pipelines on Azure Databricks, leveraging Spark to process multi-terabyte delivery scan logs and real-time route telemetry for the global logistics insights platform. Developed Power BI-optimized semantic models in dbt + BigQuery, powering interactive dashboards used daily by regional ops managers to monitor fleet efficiency and warehouse throughput.

Databricks Spark Power BI DBT BigQuery Apache Airflow Azure DevOps Confluence

Senior Data Engineer

Flatiron Health

Jul 2019 - Oct 2022 (3 years 3 months)

Built and maintained dbt models on Redshift to structure patient, encounter, and treatment data for Flatiron's oncology research platform, powering dashboards used in trial design and regulatory reporting. Developed Spark-based batch pipelines in Databricks to ingest and normalize high-volume EHR and lab data from 30+ provider networks, ensuring consistency across fragmented source systems.

DBT Redshift Spark Databricks Apache Airflow Great Expectations AWS Glue S3 Lambda

Data Engineer

Stripe

Sep 2017 - Jul 2019 (1 year 10 months)

Rebuilt the revenue data modeling layer by migrating fragmented SQL logic into modular dbt models in Redshift, enabling consistent financial reporting and reducing maintenance workload. Developed and maintained Airflow DAGs to orchestrate payment lifecycle pipelines, with automated alerting and rollback capabilities to support finance-critical workflows.