Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.
Summary
The Analytics Engineer III is a senior individual contributor role within BIT Hyderabad, owning the design, build, and operation of both data engineering and ML engineering systems that power analytics, data science, and AI/ML at scale across BMS. The AE-3 is hands-on and execution-focused — delivering enterprise-grade data products, ML pipelines, and platform infrastructure while collaborating closely with US counterparts, data scientists, and platform teams. They also contribute to team standards, code reviews, and junior engineer growth as a natural part of the role.
Roles & Responsibilities
Data & Lakehouse Engineering
Design and operate end-to-end data products — ingestion → medallion architecture → transformation → serving → CI/CD → observability — on Databricks at enterprise scale
Build production-grade Lakehouse pipelines using Delta Lake (OPTIMIZE, ZORDER, liquid clustering, CDF), Unity Catalog, Workflows, Delta Live Tables, and Structured Streaming
Deploy using Databricks Asset Bundles (DABs); write modular Python code with secure credential management via service principals, secret scopes, and IAM
Define and enforce data engineering standards — versioned pipelines, data contracts, automated quality gates, lineage, and standardized project templates
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Design and operate end-to-end ML pipelines — feature engineering, model training, evaluation, deployment, serving, and monitoring — with emphasis on scalability and reliability
Build and maintain MLOps platform components — experiment tracking, model registries, CI/CD for ML, feature stores, and containerized environments
Define CI/CD strategy for ML — model validation gates, canary/shadow deployments, automated rollback, and high-availability inference patterns
Manage production ML pipeline schedules across batch and real-time inference — SLA adherence, issue triage, and incident resolution
Observability & Platform
Architect observability across data and ML systems — Great Expectations, Pandera, Evidently, Databricks Lakehouse Monitoring, Prometheus, Grafana — covering data quality, model drift, and SLAs/SLOs
Lead cloud migration and modernization to AWS, Databricks, and Kubernetes-based architectures
Develop reusable libraries, templates, and frameworks to reduce engineering toil for data scientists and peers
Leverage AI tools (Claude Code, Copilot) to accelerate delivery and build reusable skills/agents
Collaboration & Standards
Partner with Data Science, MLOps, IT, and US counterparts on execution, planning, and delivery
Conduct code and design reviews; contribute to team standards and help unblock peers
Ensure compliance with GxP, HIPAA, and pharmaceutical data governance standards with Unity Catalog as the governance backbone
Communicate technical decisions clearly through documentation, runbooks, and RFCs
If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Uniquely Interesting Work, Life-changing Careers With a single vision as inspiring as “Transforming patients’ lives through science™ ”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
On-site Protocol
BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:
Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
Supporting People with Disabilities
BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your ar
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