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Cullen Gentzyel

@cullengentzyel

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Senior software engineer building HIPAA-aware data platforms for genomics, bioinformatics, and healthcare analytics.

United States

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What I'm looking for

I’m looking to build production-grade data platforms and pipelines for regulated healthcare and genomics—privacy-preserving, well-governed, and observable—turning raw clinical and multi-source data into reliable analytics-ready datasets and APIs.

I’m a Senior Software Engineer with 5 years of experience designing, building, and maintaining production data products for genomics research, bioinformatics, and healthcare diagnostics—inside HIPAA-regulated environments. I help teams translate scientific and clinical requirements into scalable, analytics-ready datasets while keeping privacy, compliance, and data governance at the center.

Across my roles, I’ve led pipeline and platform work from raw clinical and multi-source healthcare data to curated outputs, using Python and orchestration tools like Airflow and Prefect. I’ve built distributed processing systems with Spark (PySpark/Spark SQL), implemented privacy-preserving de-identification, and delivered reliable data services/APIs (FastAPI and Node.js) with lineage, observability, validation, and reproducibility baked in.

Experience

Work history, roles, and key accomplishments

Senior Data & Analytics Engineer

Jera

Jan 2023 - Nov 2025 (2 years 10 months)

Designed and operated a production-grade HIPAA-aware data platform for healthcare genomics and clinical/research data integration, delivering analytics-ready datasets for translational science and oncology use cases. Built distributed ingestion and transformation systems with privacy-preserving de-identification, data governance (lineage/traceability/observability), and API services for secure ana

Python Apache Airflow BigQuery HIPAA compliance Data Lineage Data Validation fastAPI

Data Engineer

Jera

Jun 2021 - Dec 2022 (1 year 6 months)

Built and maintained ETL pipelines that integrated healthcare-adjacent, clinical, and operational data into analytics-ready datasets for reporting and analytics workflows. Implemented data modeling and Spark/SQL transformations with incremental/full-load processing, plus data quality validation and monitoring for reliable regulated-data handling.

Python Apache Airflow Data Modeling Snowflake BigQuery Data Validation