Data Engineer
About the role
Our data team is organized across three groups: Data Engineering, Data Science, and Strategic Analytics. Data Engineering owns the warehouse, the orchestration layer, and the pipelines that move data from our operational systems to everyone who depends on it. This year, with the credit portfolio scaling and our modeling needs getting heavier, focus areas include real-time event ingestion, the risk decisioning service redesign, AI-agent data access on Redshift Serverless, ERP/EDI standardization with Finance and Accounting, and AI-assisted workflows across the engineering lifecycle.
Data Engineers partner directly with Engineering, Risk, Commerce, Accounting, and Compliance, owning both the platform infrastructure and the business problems it's built to solve.
Requirements
- Two years of production data engineering experience in a comparable environment
- Comfort moving across SQL, Python, orchestration, and infrastructure-as-code without needing one of them to be your specialty
- Experience with AWS throughout, Redshift and Spectrum for the warehouse, Glue and Fivetran for ingestion, Airflow for orchestration, ECS/ECR for services, DMS for replication, DataHub for cataloging and lineage, Terraform to hold it all together
- Experience with Python and SQL
Qualifications
- Experience with a variety of data engineering tools and technologies
- Strong problem-solving skills and ability to work independently
- Excellent communication and collaboration skills
- Ability to work in a fast-paced, dynamic environment