Key skills
PythonSQLAIELTData EngineeringData WarehousingAnalyticsBISnowflakedbtAzureAzure DevOpsGitGitHubVersion ControlCI/CDLeadershipCommunicationCollaborationSales
About this role
DriveTime Family of Brands is the largest privately owned used car sales finance & servicing company in the nation. They are seeking a Senior Data Engineer to lead the development, optimization, and governance of data transformation and modeling processes, enabling analytics and business teams with high-quality data products.
Responsibilities:
- Lead the design and development of robust dbt Core models to transform raw data into trusted, analytics-ready datasets in Snowflake
- Architect scalable and performant data models that align with business needs and support enterprise reporting, analytics, and AI initiatives
- Collaborate across BI, analytics, and business teams to gather requirements and translate them into efficient ELT solutions
- Implement data quality frameworks, documentation standards, and lineage tracking to ensure transparency and trust in our data ecosystem
- Use Python to support automation, data validation, and performance monitoring across ELT pipelines
- Monitor and optimize Snowflake query performance and cost efficiency
- Guide and mentor other engineers, promoting skill development in dbt, CI/CD, and modern data architecture
- Provide thought leadership on modern data transformation practices, helping to shape strategy, tooling, and best practices for the enterprise
- Support data governance and metadata enrichment initiatives in alignment with enterprise data strategy
Requirements:
- 5+ years of experience in data engineering, analytics engineering
- Bachelors degree in Information Technology or related field or equivalent work experience
- Advanced SQL skills and deep experience with dbt Core for data transformation and documentation
- Expertise in Snowflake or similar modern cloud data platforms
- Proficiency in Python for scripting, automation, and performance tuning
- Strong understanding of dimensional modeling, ELT principles, and data warehousing best practices
- Experience with Git-based version control and CI/CD workflows (GitHub, Azure DevOps, Argo)
- Proven ability to lead technical projects and mentor other engineers
- Excellent collaboration and communication skills, with the ability to work across technical and non-technical teams
- Demonstrated ability to drive innovation and influence best practices in data engineering through thought leadership