About The Job

Bristol Myers Squibb is seeking an Analytics Engineer I to help build and support the analytics layer on Databricks that connects curated data to dashboards, self-service BI, and advanced analytics used across the commercial business.

Key Responsibilities

- Design, build, and support analytics-ready data products, curated datasets, and reusable transformation assets within a modern lakehouse environment to enable commercial reporting, self-service analytics, and business insights.
- Translate business and analytics requirements into explicit 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.
- Create analytics-friendly models, including fact and dimension tables, cross-domain joins, slowly changing dimensions, and business-rule-driven metrics that support dashboard, reporting, and advanced analytics consumption.
- 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.

Requirements Requirements

- 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.
- 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.

Preferred Qualifications

- Experience with Databricks, Delta Lake, or lakehouse architecture.
- Experience working with commercial pharma datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.
- Exposure to BI/reporting use cases, semantic layer design, or dashboard-ready data modeling.

Skills SQLPythonDimensional ModelingETLData QualityDatabricks

Benefits

- Wellness programs

📌 Analytics Engineer I - Commercialization (Hyderabad)
🏢 Workowon
📍 Hyderabad