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Principal Data Engineer

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Overview

In this role you will lead the strategic design and hands-on delivery of a next-generation Object-Centric Data Fabric, unifying multi-stream clinical data into a centralized semantic model. You’ll drive the evolution of data lake and lakehouse architectures, powered by AI-augmented workflows, to accelerate trials and enable scalable analytics. You’ll collaborate with cross-functional teams to deliver high-impact platform capabilities while safeguarding data integrity and regulatory compliance.

Pay / Benefits
  • medical insurance
  • dental insurance
  • life and disability insurance
  • generous pension
  • 25+ paid holidays
  • hybrid work arrangement
Responsibilities
  • Architect and evolve enterprise semantic data fabric across multi-stream clinical data
  • Design and implement a modern Data Lake using Apache Iceberg with Snowflake interoperability
  • Develop end-to-end ingestion pipelines for complex clinical trial schemas
  • Build real-time streaming pipelines with Kafka on AWS and Snowflake
  • Apply AI-assisted schema inference, mapping, and code generation to speed integration
  • Drive technical direction on CDC, clustering, data migration, and performance optimization
  • Integrate AI inferencing into data pipelines for real-time telemetry anomaly detection
  • Lead TDD/BDD initiatives and generate AI-assisted validation artifacts and compliance documentation
  • Troubleshoot distributed data environments and build resilient, self-healing pipelines
Key requirements
  • Expert SQL (OLAP/OLTP) and Snowflake data platform mastery
  • Proven backend experience in Java or Scala on AWS
  • Experience with Apache Kafka and real-time streaming architectures
  • AI-enabled development tools integration (e.g., GitHub Copilot, Cursor)
  • CI/CD, Git for version control, and AI-assisted testing/documentation
  • Knowledge of clinical trial data workflows and regulatory standards (GxP, HIPAA, GDPR)
  • Experience with data lake architectures and Apache Iceberg
  • Familiarity with data governance, data lineage, and audit documentation
  • leadership and strategic thinking
  • cross-functional collaboration
  • problem-solving and analytical thinking
  • Snowflake
  • Apache Iceberg
  • Kafka

Skills

See also

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