Team Lead - Data Modeling

Job title: Team Lead - Data Modeling

Holman is a family-owned, global automotive services organization anchored by our deeply rooted core values and principles that have enabled us to continue Driving What’s Right throughout the last century. Our teams deliver the Holman Experience by treating our customers and each other as we would like to be treated, and creating positive, rewarding relationships all around.

The automotive markets Holman serves include fleet management and leasing; vehicle fabrication and upfitting; component manufacturing and productivity solutions; powertrain distribution and logistics services; commercial and personal insurance and risk management; and retail automotive sales as one of the largest privately owned dealership groups in the United States.

Position Description:

• Data Architecture & Modeling

• Lead the design and implementation of enterprise data models and business-ready data products within a modern Lakehouse architecture.

• Design scalable Medallion Architecture solutions across Bronze, Silver, and Gold layers.

• Develop Gold-layer business models that provide trusted, reusable, and governed enterprise data assets.

• Design semantic models and business-layer abstractions that provide consistent access to enterprise data.

• Create data structures optimized for analytics, operational applications, APIs, machine learning, generative AI, and agentic workflows.

• Development & Engineering

• Develop and optimize transformation frameworks using technologies such as Databricks, dbt, Delta Lake, Spark, and SQL.

• Remain actively involved in hands-on data modeling, transformation design, and technical implementation.

• Develop reusable modeling patterns, frameworks, and standards that accelerate delivery across teams.

• Apply automation, metadata-driven approaches, and AI-assisted development tools to improve productivity, code quality, documentation, and solution quality.

• Technical Leadership

• Serve as a technical leader and subject matter expert for enterprise data modeling and transformation.

• Establish and maintain modeling standards, naming conventions, development practices, and reusable architecture patterns.

• Lead architecture and design reviews to ensure solutions are scalable, maintainable, performant, secure, and cost-effective.

• Mentor data modelers, data engineers, and analytics engineers through technical coaching, design reviews, and knowledge sharing.

• Identify technical risks involving performance, scalability, maintainability, cost, and data quality and guide teams toward appropriate solutions.

• Data Quality, Governance & Trust

• Embed data quality, lineage, governance, observability, security, privacy, and compliance into the data modeling lifecycle.

• Help establish clear standards around data ownership, governance, and domain responsibilities.

• Ensure enterprise data products are trusted, discoverable, reusable, and optimized for both human and AI consumption.

• Collaboration & Innovation

• Partner with business stakeholders, solution architects, data engineers, analytics engineers, application teams, analytics teams, and AI practitioners to translate business requirements into scalable data products.

• Facilitate technical design discussions across multiple stakeholder groups and communicate complex architecture concepts to both technical and non-technical audiences.

• Evaluate emerging cloud data, AI, automation, and agentic technologies and identify opportunities where they can deliver meaningful business value.

• Build proofs of concept and help establish new architectural approaches where established patterns do not yet exist.

Required Education & Experience:

Minimum Education:

Bachelor’s degree in computer science, Information Systems, Data Engineering, Data Science, Software Engineering, or a related field

Preferred Education & Experience:

Master’s degree in computer science, Data Engineering, Artificial Intelligence, Analytics, or related disciplines.

Relevant Work Experience:

• 10+ years of experience designing and implementing modern cloud data platforms, data warehouses, lakehouses, or enterprise analytics environments.

• Strong experience with Databricks, Delta Lake, Spark, dbt, SQL, and cloud-native data engineering technologies.

• Experience designing Medallion Architecture solutions and implementing bronze, silver, and gold layer patterns.

• Experience building scalable data products, semantic models, and analytics-ready datasets for enterprise consumption.

• Strong understanding of data transformation frameworks, ELT architectures, metadata

• Familiarity with modern AI technologies, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector-based architectures, and agentic workflows.

• Experience leveraging AI-assisted development tools and modern engineering practices to improve productivity and solution quality

Equal Opportunity Employment and Accommodations

Holman provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you are a person with a disability needing assistance with the application process, please contact HR at our designated channel.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.