We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. Design, build, and support analytics-ready data products, curated datasets, and reusable transformation assets within a modern lakehouse workplace to enable commercial reporting, self-service analytics, and business insights.

Translate business and analytics requirements into clear data specifications, dimensional models, metrics definitions, and dataset readiness criteria aligned to internal modeling and delivery standards.

Develop and maintain scalable SQL- and Python-based transformation logic that integrates structured and semi-structured pharma datasets such as claims, patient, sales, payer, HUB, and specialty pharmacy data.

Apply internally developed accelerators, reusable code patterns, templates, and engineering guardrails to improve development speed, consistency, and maintainability across data products.

Implement standardized data quality checks, reconciliation logic, validation routines, and anomaly detection controls to ensure datasets are accurate, complete, and trusted by downstream users.

Document data products, metric definitions, lineage, assumptions, and known limitations in accordance with internal documentation and governance standards.

Work as part of a deployed engineering team embedded alongside an assigned Commercial business domain, partnering with data engineers, analysts, BI developers, and business stakeholders to support dashboard and reporting use cases.

Apply data governance standards, access controls, and compliant handling practices for sensitive and regulated data, including PII/PHI awareness.





Strong proficiency in SQL for analytics transformations, data modeling, validation, and performance tuning.

Working knowledge of Python for data preparation, validation, automation, and analytical workflows.

Experience developing analytics-ready datasets using dimensional modeling concepts such as facts, dimensions, grains, keys, and slowly changing dimensions.

Familiarity with ETL/ELT patterns, lakehouse concepts, and medallion architecture, including bronze, silver, and gold/refined layers.

Experience with data quality practices including profiling, cleansing, standardization, reconciliation, and anomaly detection.

Working knowledge of governance and secure data handling practices, including documentation, lineage, and access controls.

Familiarity with BI/visualization tools such as Tableau or Power BI.

Willingness to work as part of a deployed team embedded within a business domain, learning to adapt to domain-specific priorities.

Qualifications & Experience

- A bachelor's or master's degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, Analytics, or a related field (or equivalent practical experience).
- 1–3 years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.




- Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance.
- Preferred: experience with Databricks, Delta Lake, or lakehouse architecture.
- Preferred: experience working with commercial pharma datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.
- Preferred: exposure to BI/reporting use cases, semantic layer design, or dashboard-ready data modeling.

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. 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 [View email address on joinrs.com Protection We will never request payments, financial information, or social security numbers during our application or recruitment process. Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

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📌 Analytics Engineer (Remote) (Hyderabad)
🏢 Bristol-Myers Squibb
📍 Hyderabad