Senior Data Engineer (DBT)

What’s Under the Hood

DriveTime Family of Brands is the largest privately owned used car sales finance & servicing company in the nation. Headquartered in Tempe, Arizona and Dallas, Texas, we create opportunities and improve the lives of our customers and our employees by placing a focus on putting the right customer, in the right vehicle, on the right terms and on their path to ownership.

The DriveTime Family of Brands spans across DriveTime, Bridgecrest and SilverRock.  You can find us at the intersection of technology and innovation as we use our proprietary tools and over two decades of industry knowledge to redefine the process of purchasing, financing, and protecting your vehicle. 

That’s Nice, But What’s the Job?

This is not a position for which sponsorship will be provided. Individuals with temporary visas or who need sponsorship now or in the future are not eligible for hire at this time.

In short, this role sits within our centralized Data Services organization and is responsible for designing, building, and delivering scalable, trusted data models that power analytics, reporting, and AI initiatives across the enterprise. You’ll combine deep technical expertise in dbt Core, Snowflake, SQL, and Python with strong leadership skills, acting as both a hands-on contributor and a mentor who raises the bar for modern data transformation practices. This is a highly collaborative role, working closely with engineers, analysts, business partners, and leadership to turn complex data requirements into reliable, high‑impact data assets.

In long, you will be responsible for

• Owning the design and development of robust dbt Core models that transform raw data into trusted, analytics‑ready datasets in Snowflake

• Architecting scalable, high‑performance data models that support enterprise reporting, analytics, and AI use cases

• Translating complex business and analytical requirements into efficient, well‑structured ELT solutions through close collaboration with BI, analytics, and business stakeholders

• Embedding best practices in data quality, testing, documentation, and lineage to ensure transparency, reliability, and trust in our data ecosystem

• Leveraging Python to support automation, data validation, orchestration, and performance monitoring across ELT pipelines

• Monitoring, tuning, and optimizing Snowflake query performance and cost efficiency

• Leading technical design discussions and contributing hands‑on to critical data initiatives

• Serving as a technical lead and mentor, guiding other engineers and elevating standards across the full data transformation lifecycle

• Providing thought leadership on modern data transformation patterns, tooling, and architecture to help shape enterprise data strategy

• Supporting data governance and metadata enrichment initiatives in alignment with broader enterprise data goals

So What Kind of Folks Are We Looking For?

• Collaborative leaders who enjoy partnering across engineering, analytics, and business teams

• Clear communicators who can explain complex technical concepts to both technical and non‑technical audiences

• Mentors who are passionate about developing others and fostering a culture of continuous learning

• Strategic thinkers who balance long‑term architecture with near‑term business needs

• Problem solvers who take ownership, drive innovation, and influence best practices across the organization

The Specifics.

• 5+ years of experience in data engineering or analytics engineering

• Bachelor’s degree in Information Technology or a related field, or equivalent practical experience

• Advanced SQL skills with deep, hands‑on experience using dbt Core for data transformation, testing, and documentation

• Experience with dbt Core

• Strong expertise with Snowflake or a similar modern cloud data platform

• Proficiency in Python for scripting, automation, and performance tuning

• Solid understanding of dimensional modeling, ELT principles, and data warehousing best practices

• Experience with Git‑based version control and CI/CD workflows (e.g., GitHub, Azure DevOps, Argo)

• Demonstrated ability to lead technical initiatives and mentor other engineers

• Strong collaboration skills and a proven ability to influence and drive adoption of modern data engineering best practices

Nice to have

• Experience supporting enterprise data governance or metadata management initiatives

• Prior involvem