Analytics Engineer I, Commercialization

Develop and maintain curated, analytics-ready datasets and reusable transformation assets within a Databricks lakehouse environment for commercial reporting and self-service BI.

Translate business and analytic requirements into dimensional data models, metric definitions, and scalable SQL/Python transformations focused on commercial pharma data.

Ensure data quality, documentation, governance, and collaborate closely with a deployed engineering team supporting an assigned Commercial business domain.

Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent practical experience).

1–3 years of experience in analytics engineering, data engineering, or BI engineering involving curated datasets and analytics-ready assets.

Proficiency in SQL and working knowledge of Python for data transformations; experience with dimensional modeling and data quality practices.

Experience or familiarity with Databricks, Delta Lake, or lakehouse architecture preferred; experience with commercial pharma datasets preferred.

Early-career engineer with hands-on experience building scalable data products and familiarity with modern lakehouse concepts in a commercial pharma context.

Operates effectively as part of an embedded cross-functional team partnered with business stakeholders within a specific commercial domain (e.g., Sales, Marketing).

Detailed-oriented with strong focus on data quality, documentation, governance, and applying engineering best practices in an analytics environment.