Senior Manager & Tech Lead, Translational Data Engineering & AI

Career CategoryClinical DevelopmentJob DescriptionLocation: Amgen India office, HyderabadEmployment type: Full-timeDepartment / Team: Computational biology team in Precision MedicineHigh level roleWe 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 responsibilitiesIndependently 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 modelsDesign and implement AI enabled tools for maximal automation and troubleshooting of data ingestion processesIn coordination with the technology organization, define, design and implement metadata curation & management toolsLead the configuration and setup for MCP servers to manage data interfacesServe as an SME for agentic orchestration frameworks pan R&D, working close with technology, AI&D and other R&D functionsManage 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 qualificationsEducation & experienceBachelor’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 skillsWell-versed in agentic automation, metadata management, and AI-enabled ETL processesStrong programming skills in Python and database design. Experience with DatabricksExperience 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 processingKnowledge 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 vocabulariesStrong data modeling and metadata management skills; familiarity with data catalogs and lineage toolsExperience leading cross-functional technical projects and mentoring engineers. Excellent stakeholder management and communication skills.Prior experience in a biomedical/pharmaceutical environment.