Support project teams in the design, development, and delivery of RWD solutions across multiple databases.
Manage the inflow of diverse healthcare data sources and ensure data quality.
Develop technical specifications and transform data into a common data model.
Publish validated datasets for enterprise-wide use.
Provide reports, presentations, and technical explanations to epidemiologists, analysts, and programmers.
Communicate with data vendors and ensure accountability for data quality.
Help ensure quality standards and evaluate new methodologies.
Perform SQL querying, transformation, and quality control.
Apply SAS, Python, and programming tools to support analytical workflows.
Work with real-world healthcare datasets (Optum, PharMetrics, Flatiron, registry data).
Support OMOP data model conversions.
Leverage AI tools such as Databricks Genie and MS Copilot.
Work independently or as part of a team.

Bachelor’s degree in Data Engineering, Computer Science, Statistics, Mathematics, or related field.
1–2 years of SAS statistical programming experience.
5 years of Python programming experience.
Experience with SQL querying and data transformation.
Experience with real-world healthcare data (Optum, PharMetrics, Flatiron, Registry databases).
Experience with OMOP specifications and conversions.
Experience communicating with data vendors.
Proficiency leveraging AI tools (Databricks Genie, MS Copilot).
Ability to work independently and collaboratively.
Self-starter with strong time management.

RWD Data Engineer

Key skills