Senior Data Modeler

Credit Acceptance is proud to be an award-winning company with local and national workplace recognition in multiple categories! Our world-class culture is shaped by dedicated Team Members who share a drive to succeed as professionals and together as a company. A great product, amazing people and our stable financial history have made us one of the largest used car finance companies nationally. Our Engineering and Analytics Team Members utilize the latest technology to develop, monitor, and maintain complex practices that help optimize our success. Our Team Members value being challenged, are encouraged to express their ideas, and have the flexibility to enjoy work life balance. We build intrinsic value by partnering with all functions of our business to support their success and make strategic business decisions. We focus on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture! The Senior Data Modeler designs and evolves high-quality data models across our modern data platform. This role combines strong hands-on modeling expertise with growing involvement in AI-forward data practices-including semantic layers, enriched metadata, and structured data descriptions that enable AI systems to work with enterprise data effectively. This position will operate as a key contributor within the Data Engineering team, translating business requirements into well-governed logical and physical models that serve analytics, reporting, and emerging AI use cases. While architectural strategy and enterprise standards are set by the Principal Data Engineer and VP of Data Engineering, it will be a critical partner in executing that vision-bringing strong modeling judgment, cross-system awareness, and a willingness to engage with modern semantic and AI-adjacent concepts. This is not a narrow, single-project role. This position thinks across the data lifecycle-from systems of record through the lakehouse to downstream consumers-and who can grow into increasing ownership of semantic and AI-ready data design over time. Outcome and ActivitiesThis position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member

Data Modeling and Design:

Design and maintain logical and physical data models (dimensional, relational) across our Databricks lakehouse environment. Apply Kimball star schema and normalized modeling best practices. Translate business requirements into clear, well-documented data structures that serve analytics, reporting, and AI consumption.

Cross-System Data Lifecycle Awareness:

Model data with awareness of the full lifecycle-from systems of record through integration layers to lakehouse and downstream consumers. Ensure models account for how data originates, flows, and is consumed across multiple systems, not just within the big data platform.

Semantic Layer and AI-Ready Data:

Support the development of semantic layer artifacts (curated views, conformed dimensions, governed metrics, Genie-ready configurations) that enable AI agents and self-service analytics to interpret enterprise data correctly. Partner with the Principal Data Engineer to evolve metadata practices toward richer, machine-interpretable descriptions-business definitions, relationships, and constraints.

Metadata and Business Glossary:

Contribute to critical data element identification, business glossary development, and data dictionary maintenance. Help explore approaches to reduce manual cataloging effort through AI-assisted tooling and programmatic metadata generation.

Collaboration and Delivery:

Partner with data engineers to implement models in performant ELT pipelines and denormalized views (such as Dealer Datahub patterns). Participate in design reviews, provide modeling guidance during development, and work cross-functionally with business stakeholders and analytics teams.

Governance and Standards:

Adhere to and help refine enterprise data modeling standards, naming conventions, and design patterns within the SDLC. Support model review processes, change management, and data quality efforts. Identify opportunities to improve modeling approaches or reduce duplication.

Competencies:

The following items detail how you will be successful in this role.

Customer Empathy:

Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience.

Engineering Excellence:

Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions.

One Team:

A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively.

Owner's Mindset:

Owner's... For full info follow application link. Credit Acceptance is dedicated to providing an inclusive environment for all. We are proud to be an Equal Opportunity Employer and value a culturally diverse workforce. We believe in ensuring all team members demonstrate mutual respect for one another. All qualified applicants will receive consideration for employment without regard to protected characteristics like age, race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.