Senior Data Modeler

About the Role

The Senior Data Modeler will be responsible for translating business requirements into well-governed logical and physical models that serve analytics, reporting, and emerging AI use cases. This role will operate as a key contributor within the Data Engineering team, working closely with data engineers to implement models in performant ELT pipelines and denormalized views. The ideal candidate will have a strong understanding of data modeling best practices, including Kimball star schema and normalized modeling.

The company's culture is shaped by dedicated team members who share a drive to succeed as professionals and together as a company. Credit Acceptance values being challenged, encourages team members to express their ideas, and offers the flexibility to enjoy work-life balance. The company focuses on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture.

What You Will Do

• Design and maintain logical and physical data models (dimensional, relational) across the Databricks lakehouse environment
• Apply Kimball star schema and normalized modeling best practices to ensure high-quality data models
• Translate business requirements into clear, well-documented data structures that serve analytics, reporting, and AI consumption
• 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
• 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, including business definitions, relationships, and constraints
• Contribute to critical data element identification, business glossary development, and data dictionary maintenance
• Explore approaches to reduce manual cataloging effort through AI-assisted tooling and programmatic metadata generation
• Partner with data engineers to implement models in performant ELT pipelines and denormalized views
• Participate in design reviews, provide modeling guidance during development, and work cross-functionally with other teams

What We Are Looking For

• 5+ years of experience in data modeling, with a strong understanding of data modeling best practices
• Experience with programmatic and Excel skills, with the ability to apply them in a data modeling context
• Strong understanding of data warehousing and ETL concepts
• Experience working with cloud-based data platforms, such as Databricks
• Strong analytical and problem-solving skills, with the ability to think critically and outside the box
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams
• Strong attention to detail, with the ability to ensure high-quality data models
• Experience with data governance and metadata management, with a strong understanding of data quality and integrity
• Familiarity with AI and machine learning concepts, with a willingness to learn and adapt to new technologies

Nice to Have

• Experience working with semantic layers and AI-forward data practices
• Familiarity with Genie-ready configurations and governed metrics
• Experience working with business glossary development and data dictionary maintenance
• Knowledge of AI-assisted tooling and programmatic metadata generation
• Experience working in a remote or distributed team environment

Benefits and Perks

• Competitive salary and benefits package
• Opportunity to work with a leading company in the used car finance industry
• Collaborative and dynamic work environment
• Professional development and growth opportunities
• Flexible work arrangements, including remote work options
• Access to cutting-edge technologies and tools
• Comprehensive health and wellness benefits
• Generous PTO and holiday schedule
• Retirement savings plan with company match
• Employee recognition and rewards program

• Tip: Make sure to highlight your experience with programmatic and Excel skills in your application, as these are key requirements for the role.
• Be prepared to provide examples of your data modeling experience, including your approach to data governance and metadata management.
• Show your passion for staying up-to-date with the latest trends in data modeling, and your willingness to learn and adapt to new technologies.
• Familiarize yourself with the company's culture and values, and be prepared to explain why you're a good fit for the team.
• Don't be afraid to ask questions during the interview process, and be prepared to provide thoughtful and well-reasoned answers to technical questions.
• Be sure to research the company and the role thoroughly, and be prepared to discuss your long-term career goals and how this role fits into your overall career aspirations.
• Consider creating a portfolio of your work, including examples of your data models and any relevant projects you've worked on.