Analytics Engineer III

Bristol-Myers Squibb; Hyderabad; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

Bristol Myers Squibb Hyderabad seeks an Analytics Engineer III to own data engineering and ML systems powering analytics at scale. The role collaborates with US teams, builds enterprise-grade data products, and supports observability and governance across data platforms.

You will contribute to standards, code reviews, and junior engineer growth while delivering reliable data pipelines and ML workflows in production.

Qualifications

• 5+ years hands-on data engineering and/or MLOps experience.

Responsibilities

• Design and operate end-to-end data products ingestion, medallion architecture, transformation, serving, CI/CD, observability at enterprise scale.
• Build production-grade Lakehouse pipelines using Delta Lake, Unity Catalog, Workflows, Delta Live Tables, and Structured Streaming.
• Define and enforce data engineering standards, versioned pipelines, data contracts, automated quality gates, lineage, and templates.
• Drive Databricks optimization, cluster sizing, Photon, autoscaling, and SQL warehouse tuning.
• Design and operate end-to-end ML pipelines, feature stores, and CI/CD for ML with scalable deployment and monitoring.
• Lead cloud migration or modernization to Databricks, AWS, or Kubernetes at scale.
• Develop reusable libraries, templates, and frameworks to reduce engineering toil for data scientists.

Skills

Databricks Delta Lake

Unity Catalog

Workflows

Structured Streaming

Python

SQL

Data modeling

MLOps

CI/CD

GxP/HIPAA

Education

Bachelor's degree in Computer Science/related field

Master's degree

Ph.D. in a data-focused field

Tools

Databricks

MLflow

Dagster

Airflow

Kedro

DVC

Polars

Pandas

DuckDB

FastAPI

BentoML

Triton

KServe

GitHub Actions

Pytest

Job description

At Bristol Myers Squibb, our employees often ask, "Who are you working for?" a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

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
• Drive Databricks optimization cluster sizing, Photon, autoscaling, and SQL warehouse tuning

ML Engineering & MLOps

• 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

Skills & Competencies

DomainKey Skills

Databricks Delta Lake, Unity Catalog, Workflows, DLT, Databricks SQL, Structured Streaming, DABs, Lakehouse Monitoring

MLOps Tooling

MLflow, Dagster/Airflow/Kedro, DVC, Feast, Hydra/OmegaConf

Cloud & Infra

AWS (SageMaker, EKS, S3, IAM) and/or Azure (AzureML, AKS, ADLS); Kubernetes; Docker

CI/CD & Hygiene

GitHub Actions, pre-commit, Ruff, nox, uv/Poetry, Pytest

Programming

Expert Python & SQL; PySpark; data modeling (dimensional, Data Vault, medallion)

Data Tooling

dbt, Polars, Pandas, DuckDB

ML Serving

FastAPI, BentoML, Triton, KServe

Monitoring

Evidently, Great Expectations, Pandara, Prometheus, Grafana

AI-Augmented

Claude Code, Copilot; LLMOps, RAG, vector databases

Governance

Unity Catalog, IAM, secrets management, GxP/HIPAA

Experience

Experience Bachelor's, Master's, or Ph.D. in Computer Science, Data Engineering, Data Science, or related field

5+ years hands-on data engineering and/or MLOps experience, preferably in biopharma or life sciences

Proven track record building and owning enterprise-scale data products and ML pipelines end-to-end in production

Deep Databricks hands-on Lakehouse, Delta Lake optimization, Unity Catalog, Workflows, DABs

Experience leading cloud migration or modernization to Databricks, AWS, or Kubernetes at scale

Familiarity with healthcare clinical data, regulatory considerations (GxP, HIPAA), and pharmaceutical data governance

Experience with AI-augmented engineering tools (Claude Code, Copilot) to streamline workflows

Cross-geo collaboration with US-based teams strongly preferred

Databricks Certification (Data Engineer Associate/Professional) or cloud certification (AWS / Azure / GCP)

We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.

How We Work

Where you work matters because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

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 [e-mail]. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.

Candidate Rights

BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/

Data Protection

We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection. Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If this posting is missing required information required by local law or incorrect, contact BMS at [e-mail] with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.

R1603499 : Analytics Engineer III Data Privacy Link

We're creating innovative medicines for patients fighting serious diseases. We're also nurturing our own diverse team with inspiring work and challenging career options. No matter the role, each one of us makes a contribution. And that makes all the difference.