Clinical Data Engineer

The role

You will build the data foundation for evidence generation by designing automated pipelines that transform raw EHR data into clean research datasets. You will own data quality from ingestion through data lock and manage clinical data for studies.

What you will do

• Design and maintain version-controlled Python/SQL pipelines to transform raw EHR extracts into structured datasets.
• Reconcile disparate data models and adapt to site-specific EHR variability.
• Apply LLM and NLP techniques to extract structured clinical variables from unstructured sources.
• Drive end-to-end data management for Evidence Generation studies.
• Implement programmatic QC workflows for anomaly detection and audit trail checks.
• Build and maintain data dictionaries, EDC forms, and eCRF specifications.
• Ensure inspection-ready documentation and maintain data provenance.
• Partner with site IT and internal teams to translate EHR constraints into study data capture plans.
• Author and maintain clinical governance documents like DMPs and SOPs.
• Collaborate with Israel-based engineering and AI teams.

Required qualifications

• 5+ years in clinical research, real-world evidence (RWE), or health informatics.
• Proven ownership of research database builds, including cleaning, QC, and data lock.
• Strong SQL and Python skills for building automated ETL pipelines and programmatic QC checks.
• Hands-on experience transforming raw EHR extracts (FHIR, HL7v2, or flat-file exports) into structured, EDC-ready datasets.
• Familiarity with clinical terminologies and coding systems (e.g., ICD-10, CPT, LOINC, RxNorm) and standard health data structures.
• Experience handling data model variations across different health systems.
• Experience writing and maintaining governance collateral, including Data Management Plans (DMPs), SOPs, runbooks, and mapping specifications.
• Working knowledge of version control and reproducible-pipeline practices (e.g., Git).
• Familiarity with LLM/NLP tools for extracting structured variables from unstructured clinical text.
• Familiarity with regulated-data requirements [GCP, 21 CFR Part 11, HIPAA].

Nice to have

• Hands-on experience with major EDC platforms (e.g., REDCap, Castor, Veeva).
• Familiarity with standardized health and clinical trial data models (e.g., OMOP CDM, CDISC SDTM/ADaM, PCORnet).
• Understanding of FHIR resource structure and how EHR data is exported.

Benefits

• Medical
• Dental
• Vision
• 401(k)
• Generous vacation
• Dental insurance (Israel)
• Performance-based bonuses (Israel)
• Cibus meal allowance (Israel)
• Meals at the office (Israel)

About the company

Viz.ai is the leader in building and deploying AI-powered Care Pathways and helping doctors do their work. The Viz Platform is deployed in 2,000 hospitals across the United States and trusted by many of the leading life sciences companies.