Analytics Engineer I, Commercialization
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Job Description
Structured overview of role & requirementsAbout This Role
Develop and maintain analytics-ready datasets and transformation assets in a Databricks lakehouse environment to support commercial reporting and self-service BI.
Translate commercial business and analytics requirements into dimensional data models, metrics, and reusable data transformations with attention to data quality and governance.
Work embedded within a commercial business domain team collaborating with data engineers, analysts, and stakeholders to align data products with domain needs.
Minimum Requirements
Bachelor's or master's degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, Analytics, or related field (or equivalent practical experience).
1–3 years of experience in analytics engineering, data engineering, business intelligence engineering, or similar role building curated datasets and analytics assets.
Strong proficiency in SQL and working knowledge of Python for data transformation and validation.
Experience with commercial data sets (e.g., claims, sales, payer, patient data) and Databricks environment preferred but not strictly mandatory.
Ideal Candidate Profile
Early-career analytics engineer with hands-on experience in dimensional modeling and building curated datasets for business intelligence consumption.
Comfortable working as part of a deployed engineering team embedded in a commercial business domain such as Sales, Marketing, or Medical Affairs.
Familiarity with lakehouse architectures, data governance, data quality practices, and collaborative engineering workflows (Git, code reviews, CI/CD).