Data Engineer, Translational Data Management, Automation & AI

amgen; Hyderabad; On-site; INR 3,000,000 - 4,500,000; Full time

Job summary

Amgen India office, Hyderabad, is hiring a hands-on Translational Data Management, Automation, & AI Engineer to design, build, and operate robust data ingestion pipelines for biomarker and clinical data used in analysis, visualization, and ML for clinical trials.

Role collaborates with computational biologists, translational scientists, data scientists, and CROs to ensure timely, accurate data ingestion, quality control, and standardized data across assays and studies.

Qualifications

• 8+ years of experience with Bachelor’s in Computational Biology, AI, Computer Science, Data Engineering, or related field. PhD is a plus.
• 3+ years of experience in data engineering or platform engineering roles; clinical data exposure is desirable.

Responsibilities

• Design, implement, test, deploy, and maintain end-to-end data ingestion pipelines for biomarker and clinical data.
• Implement automated data validation, QC checks, error handling, and remediation workflows.
• Integrate Codex workflows, agentic automation and generative AI to meet TAT and efficiency goals.
• Collaborate with biomarker labs and CROs/vendors to onboard new assays; maintain data transfer specs and interfaces.
• Build and maintain harmonization/mapping logic and data models for biomarker/clinical datasets.
• Generate study-specific analysis bundles per request within defined timelines.
• Produce and maintain documentation: specs, data definitions, runbooks, onboarding guides.
• Write clean Python code and contribute to CI/CD, testing, and release processes.

Skills

Python programming

Data engineering

CI/CD practices

Team collaboration

Education

Bachelor’s degree in Computational Biology or related field

PhD is a plus

Tools

Databricks

Airflow

Nextflow

snakemake

Docker

Git

Kubernetes

AWS

Job description

Career Category

Clinical

Job Description

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

High-level role

We areseekinga hands-on, technically strongTranslational Data Management, Automation, & AI Engineerto 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, andmaintainend-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, agenticautomationand generative AI to meet TAT and efficiency goals.

• Collaborate with internal biomarker labs and CROs/vendors to onboard new assays; author andmaintaindata transfer specifications, interface control documents, and acceptance criteria.

• Build andmaintainharmonization and mapping logic (units, controlled terminology, ontologies) and data models needed to standardize biomarker and clinical datasets.

• Generatestudy-specific analysis bundle per request indefinedtimeline.

• Produce andmaintainclear 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 relatedfield. 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

• Experience working with clinical labs, biomarker assays (immunoassay, flow cytometry, immunohistochemistry, proteomics, whole genome sequencing, exome sequencing, RNA-seq, methylation, metabolomics)

• 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 workflowdevelopment and deployment, agentic automationtoolsand 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).

• Familiarity with data standardization and harmonization frameworks, controlled vocabularies

• Experience building,testingand debugging R pipelines for production data processing.

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