Senior Manager & Tech Lead, Translational Data Engineering & AI

Career Category

Clinical Development

Job Description

Location: Amgen India office, Hyderabad
Employment type: Full-time
Department / Team: Computational biology team in Precision Medicine

High level role

We are seeking a technically strong and strategically minded Manager & Tech Lead, Translational Data Engineering & AI, to own the design, implementation, and operational excellence of biomarker and associated clinical data ingestion pipelines into the precision medicine data and analytics platform. This role partners with computational biologists, translational scientists, data scientists and the technology & AI&D organizations to ensure timely, accurate, and standardized ingestion of biomarker assay data and clinical data into production systems that support biomarker analysis, visualization, and machine-learning & AI use cases for clinical trials.

Key responsibilities

• Independently lead the end-to-end design, development, and operation of data ingestion pipelines that prepare biomarker and clinical data for downstream analytics, visualization, and machine learning models
• Design and implement AI enabled tools for maximal automation and troubleshooting of data ingestion processes
• In coordination with the technology organization, define, design and implement metadata curation & management tools
• Lead the configuration and setup for MCP servers to manage data interfaces
• Serve as an SME for agentic orchestration frameworks pan R&D, working close with technology, AI&D and other R&D functions
• Manage requirements, operational aspects, delivery, and communication associated with data ingestion pipeline development and program support on biomarker objectives.
• Manage a team of data ingestion engineer independent contributors and provide technical leadership, drive best practices on software engineering.
• Collaborate with internal biomarker labs, contract research organizations, and third party labs to onboard new assays, set up data transfer specification and agreement.
• Implement data validation, quality control checks, and remediate ingestion failures and data quality issues.
• Build and maintain documentations to standardize biomarker and clinical datasets, include software specification form, data definition table, controlled terminology.
• Contribute to platform and architecture discussions and recommend improvements in architectural design, orchestration and automation.

Required qualifications

Education & experience

• Bachelor’s or Master’s degree in Computational Biology, Bioinformatics, Computer Science, Data Engineering, or related field. PhD is a plus.
• 10+ years of experience in data engineering or platform engineering roles; at least 2–3 years focused on biomarker/biological/clinical data ingestion or integration.

Technical skills

• Well-versed in agentic automation, metadata management, and AI-enabled ETL processes
• Strong programming skills in Python and database design. Experience with Databricks
• Experience with workflow/orchestration tools (e.g., Airflow, Nextflow, Snakemake).
• Familiarity with HPC, cloud platforms and storage (e.g., AWS) and best practices for secure data handling.
• Experience with version control (Git), CI/CD, containerization (Docker)
• Experience building, testing and debugging R pipelines for production data processing
• Knowledge of clinical data formats and standards (e.g., CDISC/SDTM/ADaM)
• Experience working with clinical labs, biomarker assays (immunoassay, flow cytometry, immunohistochemistry, proteomics, whole genome sequencing, exome sequencing, RNA-seq, methylation, metabolomics)
• Familiarity with data standardization and harmonization frameworks, controlled vocabularies
• Strong data modeling and metadata management skills; familiarity with data catalogs and lineage tools
• Experience leading cross-functional technical projects and mentoring engineers. Excellent stakeholder management and communication skills.
• Prior experience in a biomedical/pharmaceutical environment

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