Analytics Engineer I, Commercialization
- Location Hyderabad - TS - IN
- Experience 1-3 yrs
- Job type Full-time
- Posted 9 Oct 2026
- Qualification Bachelor's
You will be taken to Bristol Myers Squibb’s own careers page to apply. Job ID R1607232.
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.
Position Summary The Commercial Data & AI HYD team is seeking an Analytics Engineer I to help build and support the analytics layer on Databricks that connects curated data to the dashboards, self-service BI, and advanced analytics used across the business. This role is responsible for developing well-modeled datasets, metrics, and semantic assets that are easy for analysts and business users to consume. This role operates as part of a deployed engineering team, working alongside an assigned Commercial business domain (e.g., Sales, Marketing, Market Access, or Medical Affairs) under the guidance of senior engineers to help keep the analytics layer aligned with that domain's needs. The successful candidate will help analyze business and analytics requirements and build, test, and integrate the application components, tools, and utilities that support commercial reporting and analytics consumption, applying data modeling, SQL transformation, data quality, documentation, and governance practices under the guidance of senior engineers on the team. This is an early-career role that offers strong exposure to Databricks-based analytics engineering, with the opportunity to build technical depth and grow into more senior data modeling and platform responsibilities over time.