Description
**Location:** Amgen India office, Hyderabad
**Employment type:** Full-time
**Department / Team:** Computational Biology team, Precision Medicine
**High-level role**
We are seeking a hands-on, technically strong **Translational Data Management, Automation, & AI Engineer** to design, build, and operate robust biomarker and clinical data ingestion pipelines that feed our biomarker platform. You will work closely with computational biologists, translational scientists, data scientists, lab operations, and external vendors/contract research organizations (CROs) to ensure timely, accurate, and standardized ingestion of assay and clinical data for analysis, visualization, and machine-learning use cases supporting clinical trials.
**Key responsibilities**
+ Design, implement, test, deploy, and maintain end-to-end data ingestion pipelines that prepare biomarker and clinical data for downstream analytics, visualization, and ML models.
+ Implement automated data validation, quality control checks, error handling, and remediation workflows to ensure data quality and traceability.
+ Integrate Codex workflows, agentic automation and generative AI to meet TAT and efficiency goals.
+ Collaborate with internal biomarker labs and CROs/vendors to onboard new assays; author and maintain data transfer specifications, interface control documents, and acceptance criteria.
+ Build and maintain harmonization and mapping logic (units, controlled terminology, ontologies) and data models needed to standardize biomarker and clinical datasets.
+ Generate study-specific analysis bundle per request in defined timeline.
+ Produce and maintain clear documentation: software specification forms, data definition tables, runbooks, and onboarding guides.
+ Write clean, tested, maintainable Python code and contribute to CI/CD pipelines, automated testing, and release processes.
**Required qualifications**
**Education & experience**
+ 8+ years of experience with Bachelor’s in Computational Biology, Bioinformatics, AI, Computer Science, Data Engineering, or related field. PhD is a plus.
+ 3+ years of experience in data engineering or platform engineering roles; experience working with biomarker/biological/clinical data or in a clinical research environment is highly desirable.
**Technical skills**
+ **Strong programming skills in Python and database design. Experience with Databricks**
+ **Experience with workflow/orchestration tools (e.g., Airflow, Nextflow, snakemake).**
+ **Experience with agentic automation and formulation of AI workflow development and deployment, agentic automation tools and Codex workflows.**
+ **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)**
+ **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
+ Experience building, testing and debugging R pipelines for production data processing.
