Design, build, and maintain logical and physical data models across credit and lending domains, including customers, accounts, loans, balances, collateral, and payment structures
Convert business requirements into scalable architectures using dimensional, domain‑driven, and normalized modeling techniques
Partner with data engineers, analysts, and business SMEs to standardize definitions and ensure alignment with governance frameworks
Develop documentation including mappings, data dictionaries, and lineage artifacts
Optimize data models to support dashboards, regulatory reporting, analytics, and downstream consumption
Support the integration of new or evolving credit products such as mortgages, credit cards, secured lending, and revolving products
Validate model performance, scalability, and usability within Snowflake environments
Contribute to medallion‑layered architecture (bronze/silver/gold), ensuring traceability from source systems through curated layers
Requirements
5+ years in enterprise data modeling, ideally within financial services, banking, or lending
Strong understanding of credit and lending concepts (interest, balances, payments, loan lifecycle, customer/account relationships)
Hands‑on experience with ERwin Data Modeler (required)
Strong experience with dimensional modeling, 3NF, and/or data vault
Ability to interpret and reconcile complex financial data definitions across systems
Experience working with Snowflake, AWS, or other cloud data platforms
Strong collaboration and communication skills, with a disciplined documentation style
Bachelor’s degree in Data Science, Computer Science, Information Systems, Business Analytics, or a related field
Tech Stack
AWS
Cloud
Vault
Benefits
Medical, dental, vision, free tele-health, HSA with company contribution, life and disability insurance, and 401k with matching
Paid Time Off
Hybrid Work Model – Collaborate onsite in Minneapolis for alignment with engineering and business partners
Career Development – Expand your skillset in credit data modeling, Snowflake, metadata management, and enterprise data architecture
Supportive, Structured Culture – Join a team that values clarity, governance, and consistent modeling practices