Senior Data Modeler

Credit Acceptance Corporation; Bellevue (WA); Hybrid; USD 137,000 - 191,000; Full time

Benefits offered by this job

401(K) match

Adoption assistance

Parental leave

Tuition reimbursement

Medical/dental/vision

Job summary

Credit Acceptance Corporation is seeking an experienced data modeler/architect to design and maintain dimensional and relational models across our Databricks lakehouse. You will translate business requirements into scalable structures, support AI-ready data, and collaborate with data engineers to deliver performant ELT pipelines and governed metrics.

The role requires 8+ years in data modeling or analytics engineering, strong SQL, and excellent communication.

Qualifications

• 8+ years of experience in data modeling or analytics engineering roles.
• 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; willingness to deepen semantic layer design and AI-ready data structures.
• Proficient SQL skills and experience working 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 autonomous while aligning with architectural direction.
• Experience with semantic layers, governed metrics, or analytics modeling frameworks.
• Candidates must reside in or be willing to relocate to: Southfield, MI area; Bellevue, WA area; or SF Bay Area, CA.

Responsibilities

• Design and maintain logical and physical data models across our Databricks lakehouse.
• Model data across the full lifecycle from source systems to lakehouse and downstream consumers.
• Develop semantic layer artifacts for AI-ready data and governed metrics.
• Support metadata and data dictionary initiatives, exploring AI-assisted tooling.
• Collaborate with data engineers to implement models in ELT pipelines and denormalized views.
• Adhere to enterprise data modeling standards and participate in design reviews.

Skills

Data modeling

Databricks

SQL

ELT pipelines

Communication

Tools

ER/Studio

ERwin

SqlDBM

dbt

Job description

About this job

At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact.

• 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
• 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
• 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.

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: This position offers a competitive base salary, with a range of $136,723 - $191,412.

This position is eligible for an annual variable incentive of cash and equity, between 7.5 - 15% of base salary. Actional amounts are based on individual performance.

Final compensation within the range is influenced by many factors including assigned hub location, role-specific skills, depth and experience level, industry background, relevant education and certifications.

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.

• 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
• 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.

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 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.

California Residents: Please click here for the California Consumer Privacy Act (CCPA) notice regarding the personal information Credit Acceptance may collect from you.

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