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High competition from strong employer brand, mid-level generalist role, Hyderabad metro, and broad MLOps/Databricks requirements.
Medium — core data engineering skills transfer across industries, though biopharma and clinical-data experience is advantageous.
High due to explicit 5+ years, required Databricks/AWS/MLOps skills and regulated biopharma expectations.
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Design, deploy, and maintain scalable, reliable data pipelines and MLOps solutions for data science products in biopharma.
Develop tools and frameworks to enhance data scientists' productivity and collaborate closely to implement ML engineering best practices.
Analyze large-scale, structured and unstructured healthcare and clinical trial data to generate actionable insights enhancing business innovation and performance.
Typically 5+ years of experience in data engineering, preferably within biopharma/pharmaceutical industry.
Master's or Ph.D. in Data Engineering, Statistics, Computer Science, or related discipline.
Proficiency in Databricks, AWS, Python or R, and experience with ML, MLOps, and data engineering methods.
Experience handling large-scale structured and unstructured healthcare-related data and deploying machine learning algorithms.
Experienced in biopharma domain with understanding of clinical trial design, healthcare data sources and regulatory constraints.
Strong technical skills in cloud platforms and big data technologies aligned with ML and data engineering operations.
Able to mentor junior engineers and work cross-functionally to drive data science and ML integration into business solutions.