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2 days ago
We are seeking an experienced Data Engineering Specialist to join our team. This role is responsible for designing and implementing intelligent frameworks for synthetic and automated test data generation in support of clinical trials, regulatory submissions, and GxP-compliant systems.
Key Responsibilities:
Synthetic Test Data Automation- Design and develop Python frameworks to generate synthetic clinical and operational datasets.
- Produce CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Simulate domain-specific datasets (adverse events, labs, demographics, drug exposure) with variability and referential integrity.
- Develop connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows.
- Apply generative AI (LLMs, GANs, diffusion models) to model realistic clinical scenarios.
- Create synthetic patient journeys across EDC, eCOA, CTMS, LIMS, and PV systems.
- Use AI-driven automation to simulate rare or complex cases for stress and edge-case testing.
- Ensure adherence to GxP, 21 CFR Part 11, HIPAA, and GDPR standards.
- Implement anonymization/obfuscation while maintaining clinical and statistical fidelity.
- Produce validation protocols and documentation for audit and inspection readiness.
- Work with Clinical Data Management, Biostatistics, Pharmacovigilance, and Compliance teams to gather requirements.
- Embed test data generation into CI/CD pipelines, trial simulations, and automated validation environments.
- Partner with SMEs to validate AI-generated datasets for regulatory acceptability.
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