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Senior Data Modeler

Credit Acceptance
Remote, USARemoteData & AnalyticsSenior-Level$114,000 - $167,000Posted: today

About the role

Credit Acceptance is proud to be an award-winning company recognized both locally and nationally across multiple workplace categories. Our world-class culture is shaped by dedicated team members who are driven to succeed as professionals individually and together as a team. Backed by a strong product, exceptional people, and a stable financial foundation, we’ve grown into a leading provider of used and new car financing across the country. 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.

This position follows a hybrid work model, offering two work-from-home days and three standard in-office days each week with the team and key stakeholders at the local office. Outcome and Activities 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 Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business.

Requirements: 8+ years of experience in data modeling, data architecture, or analytics engineering roles Strong hands-on expertise in dimensional modeling (Kimball) and relational modeling (3NF) Experience modeling data across multiple source systems in cloud data platforms (Databricks or similar) Awareness of how data models serve downstream AI and analytics use cases, with willingness to deepen expertise in semantic layer design and AI-ready data structures Proficient SQL skills and experience working closely with data engineers on ELT pipelines Experience with data modeling and design

tools (ER/Studio, ERwin, SqlDBM, dbt, or similar) Understanding of data governance concepts including lineage, metadata management, and data quality Strong communication skills and ability to collaborate across technical and business teams Self-directed and comfortable operating with autonomy while working within established architectural direction Experience with or exposure to semantic layers, governed metrics, or analytics modeling frameworks Preferred: Familiarity with metadata management platforms, data catalogs, or data documentation tools (e.g., Collibra, Unity Catalog) Awareness of

knowledge graphs, ontologies, or formal data description frameworks (OWL, RDF)—deep expertise not required, but curiosity and willingness to learn is essential Hands-on Databricks experience including Unity Catalog, Delta Lake, and lakehouse architecture patterns Familiarity with Data Vault methodology Experience in financial services, auto lending, or regulated industries Exposure to AI-assisted tooling for metadata, documentation, or data profiling tasks Target Compensation: A competitive base salary range from $114,000 – $167,000.

This position is eligible for an annual variable cash bonus, between 7.5 - 15%. Bonus amounts are based on individual performance. Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications. Candidates must reside in or be willing to relocate to one of the following hub locations: the greater Southfield, Michigan, area; the greater Bellevue, Washington, area; or the San Francisco Bay Area, California.

INDENGLP #zip #LI-Hybrid Benefits Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work Our Company Values: To be successful in this role, Team Members need to be: Positive by maintaining resiliency and focusing on solutions Respectful by collaborating and actively listening Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions Direct by

effectively communicating and conveying courage Earnest by taking accountability, applying feedback and effectively planning and priority setting Expectations: Remain compliant with our policies processes and legal guidelines All other duties as assigned Attendance as required by department Advice! We understand that your career search may look different than others. Our hiring team wants to make sure that this would be a fit not just for us, but for you long term. If you are actively looking or starting to explore new opportunities, send us your application! P.S.

We have great details around our stats, success, history and more. We’re proud of our culture and are happy to share why – let’s talk! Required degrees must have been earned at institutions of Higher Education which are accredited by the Council for Higher Education Accreditation or equivalent. Credit Acceptance is dedicated to providing a safe and inclusive working environment for all. As part of our Culture of Compliance, we are proud to be an Equal Opportunity Employer and value our culturally diverse workforce.

All qualified applicants will receive consideration for employment regardless of the person’s age, race, color, religion, sex, gender, sexual orientation, gender identity, national origin, veteran or disability status, criminal history, or any other legally protected characteristic. California Residents: Please click here for the California Consumer Privacy Act (CCPA) notice regarding the personal information Credit Acceptance may collect from you. Play the video below to learn more about our Company culture.

At Credit Acceptance, our mission is to provide people with access to the vehicles they need, regardless of their credit history. Working with thousands of dealer partners nationwide, we help make vehicle ownership possible while creating value for our customers, dealer partners, Team Members, and communities. We celebrate what makes each of us unique. We want every Team Member to feel comfortable bringing their authentic self to work because diverse perspectives make us stronger.

Through an inclusive culture, opportunities for growth, and a commitment to well-being, we support Team Members in bringing their best to work each day.

Credit Acceptance offers Team Members: Competitive compensation, including bonus and profit-sharing opportunities Comprehensive benefits that support your health, well-being, and financial future Technology, tools, and resources designed to help you do your best work Opportunities to make an impact while helping customers, dealer partners, and communities succeed A collaborative culture where diverse perspectives, curiosity, and new ideas are valued Meaningful career growth through internal mobility, development, and learning opportunities Flexible work options, including remote, hybrid, and

onsite opportunities based on team To learn more about who we are and what makes us a Great Place to Work, follow this link! If you are a current Credit Acceptance Team Member, click here to apply.

Minimum requirements

  • 8+ years in data modeling, architecture, or analytics engineering with strong dimensional (Kimball) and relational (3NF) modeling skills
  • Experience with cloud data platforms (Databricks or similar), proficient SQL, and data modeling/design tools
  • Strong communication, collaboration skills, and understanding of data governance, metadata, and AI-ready data structures

This listing was parsed by AI and may not be complete. Check the official posting on Credit Acceptance's site for the most accurate information.

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