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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, general Data Engineer title, and metro Pune increase candidate competition.
Role requires deep clinical trial and GxP expertise, making cross-industry transfers difficult.
Requires clinical GxP domain expertise and specific data engineering plus AI/LLM tooling, raising filter strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead design, development, and maintenance of scalable, robust data pipelines and infrastructure for Pharma R&D clinical trial data.
Build and optimize ETL/ELT processes and data storage solutions (warehouses, lakes) ensuring data quality, reliability, and performance.
Collaborate closely with data scientists and clinical business stakeholders to translate requirements into technical data solutions and communicate effectively across teams.
Minimum Requirements
Experience in building and optimizing complex large-scale data engineering systems with big data technologies like Spark.
Proficiency in programming with Python or Scala and expert-level SQL skills.
Clinical domain knowledge specifically in Clinical Trial Execution processes and systems (CTMS, EDC, IxRS).
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Deep expertise in clinical trial operational data systems and data product lifecycle management with compliance (GxP standards).
Experience with advanced data architectures such as Data Mesh, semantic modeling, knowledge graphs, and AI/LLM infrastructure including RAG pipelines and relevant frameworks (LangChain, AutoGen).
Proven ability to work in product-led agile environments translating clinical operations needs into scalable data engineering solutions and communicating AI readiness to non-technical stakeholders.