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Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Own end-to-end development of production-grade data models and pipelines
- Build data quality checks, data contracts, validation logic, and monitoring
- Partner with upstream engineering teams to fix data gaps
- Support live regulatory exams, audits, and ad hoc regulator requests
- Automate recurring manual workflows into scalable pipelines and self-serve tooling
Requirements
What you’ll need- 2+ years of experience building and maintaining production data pipelines and data models
- Strong proficiency in SQL, Python, dbt, and a modern warehouse platform (Snowflake, Databricks, or similar)
- Track record implementing data quality frameworks including data contracts, validation logic, reconciliation, and monitoring
- Experience supporting time-sensitive, high-stakes data needs (regulatory exams, audits, or financial reporting)
- Demonstrated ability to turn tribal knowledge and recurring manual workflows into durable, documented infrastructure
- Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs
Benefits
Comp & perks- Health insurance
- 401(k)
- Bonus eligibility
- Equity opportunities
- Paid time off
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythondbtdata modelsdata pipelinesdata quality frameworksvalidation logicdata contractsreconciliationmonitoring
Soft Skills
collaborationproblem-solvingdocumentationattention to detailadaptability
