Responsibilities

• Understanding different aspects of the Careignition product and strategy to inform product, infrastructure and pipeline design
• Have data quality and performance top of mind while designing key engineering products
• Owning core data pipelines and products that power our industry leading insights platform
• Design, build, and maintain robust ETL/ELT pipelines, reusable components, frameworks, and libraries to process data from a variety of data sources ensuring data quality and consistency

Qualifications

• Strong programming and data engineering skills, with proficiency in distributed data processing
• Experience building data models and data pipelines on top of large datasets (on the order of 500TB to petabytes)
• Extensive experience with cloud-based data services (e.g., RDS, DynamoDB), containerized infrastructure (e.g., EKS, ECS, Docker), and data orchestration systems (e.g. Airflow, Argo, Step Functions)
• Experience working with different performant warehouses, data lakes, lakehouses; Iceberg, Redshift, Snowflake, Databricks.
• Experience with CI/CD pipelines, version control (Git), and DevOps practices in a data engineering context
• Existing background in backend development (Python/FastAPI/Django) is a big plus