Senior Data Engineer

DriveTime Family of Brands is the largest privately owned used car sales finance & servicing company in the nation. The Senior Data Engineer role involves designing, building, and delivering scalable data models that support analytics, reporting, and AI initiatives, while collaborating with various teams to ensure data quality and reliability.

Responsibilities:

• 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

Requirements:

• 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
• 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
• Experience supporting enterprise data governance or metadata management initiatives
• Prior involvement in large-scale analytics or AI-driven data platforms