We're looking for a Data Engineer to join a high-performing, collaborative engineering team focused on building and optimizing the infrastructure that powers our healthcare data platform. In this role, you'll take ownership of end-to-end data pipelines and play a key part in delivering enterprise-level data solutions that drive real-world impact.
This is a fast-paced environment where your work will directly influence the performance, scalability, and reliability of our data systems-particularly in ingesting and transforming large-scale healthcare datasets. Key Responsibilities
- Design, develop, and maintain scalable ETL pipelines using Python , SQL , and Snowflake
- Build automated, testable, and maintainable data workflows to support core analytics and reporting functions
- Leverage AWS services (e.g., S3, Step Functions, Batch, DynamoDB) to deploy and scale data applications
- Integrate data validation and unit testing into the development process
- Collaborate closely with data scientists, analysts, and engineers to deliver high-quality datasets and APIs
- Work with large healthcare data sources (including claims data) to build efficient and reliable data ingestion processes
What We're Looking For
Hands-on experience with ETL pipeline development using Python and SQLStrong working knowledge of Snowflake , Pandas , PySpark , and AWS data servicesProven ability to work with and process large datasets (1GB+) efficientlyExperience with healthcare data , particularly claims or clinical data, is strongly preferredFamiliarity with shell scripting for automation and task orchestrationDetail-oriented mindset with a focus on data quality, validation, and debuggingAbility to commit to 40 hours per week for a minimum of 6 monthsPosted by : Carter Smith
Specialization :
Data Engineering