Senior Data Engineer – Clinical Data Harness & Synthetic Data

Position: Senior Data Engineer – Clinical Data Harness & Synthetic Data

Location: Edina, MN or Chicago, IL

Duration: Long Term

Client: Elevance Health

Job Summary

Seeking a hands-on Senior Data Engineer with strong Databricks experience and specialized expertise in clinical data de-identification and synthetic data generation. The candidate will develop automated, scalable workflows to protect sensitive clinical data and generate realistic synthetic datasets for analytics, AI/ML development, testing, and research.

Required Skills:

Direct experience building or working with clinical data harnesses and automated clinical data de-identification.

Strong hands-on experience with Databricks, Apache Spark, PySpark, Python, and SQL.

Knowledge of HIPAA Safe Harbor (18 identifiers), Expert Determination, and applicable GDPR requirements.

Experience with de-identification techniques such as suppression, generalization, consistent date shifting, pseudonymization, tokenization, and cryptographic hashing.

Experience generating synthetic tabular or clinical data using techniques such as Bayesian networks, copulas, GANs/CTGAN, VAEs, or transformer/LLM-based models.

Familiarity with synthetic data tools such as SDV (Synthetic Data Vault), Gretel, or comparable frameworks.

Understanding of privacy and re-identification risk, data quality, statistical fidelity, and synthetic data utility.

Preferred Skills:

Healthcare data experience involving EHR, claims, laboratory data, clinical notes, HL7, or FHIR.

Experience scaling de-identification and synthetic data generation workflows on Spark/Databricks.

Experience with Unity Catalog, data governance, access controls, lineage, and auditability.