Data Engineer

We are seeking a Data Engineer to join our team and lead the development of our data strategy for public healthcare datasets. This role will focus on harnessing data-driven insights to advance decision-making across our organization and for our clients. The ideal candidate will possess a passion for data architecture, a strong background in public healthcare datasets, and a collaborative mindset to drive data initiatives in alignment with strategic goals. 
Key Responsibilities
Develop and execute data strategy, focusing on public healthcare datasets such as Medicare, Medicaid, and other federal and state-level data sources.
Design and maintain robust data pipelines and ETL processes to enable efficient data ingestion, transformation, and storage.
Build scalable data models that integrate public and proprietary datasets to generate actionable insights for clients.
Collaborate with internal teams, including analytics, market access, and consulting practices, to identify and address data needs.
Ensure data quality and accuracy through the implementation of rigorous QC processes and governance frameworks.
Support analytic projects by delivering clean, structured, and well-documented data to support client-driven business questions.
Stay ahead of industry trends, emerging technologies, and regulatory requirements to enhance data capabilities.


Required Skills and Experience
Education:
Bachelor’s degree in computer science, data engineering, or a related quantitative discipline. Advanced degree preferred.
Technical Expertise:
Strong proficiency in Snowflake and associated technologies
Proficiency in healthcare data architecture, with expertise in working with public datasets such as CMS data, including Medicare FFS claims, Part D PDE data, and Medicare Advantage encounter data.
Hands-on experience with programming languages such as Python, SQL, or SAS for data manipulation and analysis.
Experience integrating secondary data sources, including survey data, geographic and social determinants of health data, and drug or formulary databases.
Proficiency in building and optimizing ETL pipelines and data workflows in cloud environments (e.g., AWS, Azure).
Strong knowledge of data modeling, warehousing, and governance principles