Snowflake Data Engineer

Overview

Dealership:
Lithia Home Office

Data Engineer | Lithia & Driveway

Location:
Remote (PST work hours, preferred)

Compensation: The full salary range for this position is $80,000-$115,000 annually. The anticipated starting pay is $80,000-$110,000
, determined by factors such as skills, experience, and organizational considerations. Final compensation will be established through the interview process in accordance with applicable pay equity and transparency laws.

Lithia & Driveway (LAD) is one of the largest global automotive retailers providing a wide array of products and services throughout the ownership lifecycle with a vision to modernize personal transportation solutions wherever, whenever, and however consumers desire. With a mission of "Growth Powered by People," we are propelled by our colleagues and preferred by our customers, making Lithia & Driveway the leading automotive retailer in each of our markets.

Our success is fueled by four core values: earning customers for life, improving constantly, taking personal ownership, and having fun. Our entrepreneurial, high-performance culture sets us apart, and our philosophy is straightforward: assemble a team of passionate individuals and cultivate an environment that empowers colleagues to excel.
We’d love to have you join us on our journey!

Role Overview

The Data Engineer plays a critical role in building and maintaining the data foundation that supports analytics, reporting, and business decision-making. This position is responsible for developing, implementing, and supporting scalable data pipelines and managing data engineering workflows across modern cloud platforms. With a strong focus on automation, performance, and data quality, the Data Engineer designs, builds, and migrates ETL/ELT processes using technologies such as Azure Data Factory, Azure Synapse, and Snowflake.

Working closely with Data Architects, Data Analysts, and fellow engineers, the Data Engineer contributes to robust data ingestion, transformation, and analytics pipelines. This role receives technical direction from the Lead Data Engineer and operates primarily within Azure and Snowflake environments, partnering across teams to ensure data integrity, operational excellence, and continuous improvement.

• Design and implement data ingestion and transformation processes to load data from disparate source systems into Snowflake and downstream data platforms to enable reliable enterprise reporting and analytics.
• Migrate existing on-premises SQL Server data processes and datasets to Azure-based solutions to improve scalability, performance, and long-term maintainability.
• Integrate Azure Data Factory with Snowflake for automated data extraction, transformation, and loading processes.
• Develop, test, and maintain SQL scripts, stored procedures, and data pipelines to ensure accurate, timely, and efficient data processing.
• Ensure data is created, structured, and maintained according to established standards and documentation requirements to support data governance and usability.
• Build and configure end-to-end telemetry, alerting, and self-healing capabilities to proactively identify and resolve data pipeline issues.
• Collaborate with business stakeholders to understand requirements and translate them into effective data integration and MDM solutions.
• Implement CI/CD pipelines for data engineering projects to enhance deployment and automation capabilities.
• Ensure thorough documentation and compliance with data standards across all processes.
• Mentor and support junior team members through knowledge sharing, technical guidance, and code reviews to strengthen team capability and consistency.
• Strive for continuous improvement of code quality and development practices.
• Participate as part of a Tier-3 on-call rotation to support team-built software.

Skills

• Working knowledge of cloud-based data platforms and modern data pipeline design principles, including:
• Azure Data Services: Azure Data Factory, Synapse, Functions, Logic Apps, ADLS, and Blob Storage
• Development & Integration Tools: SSMS, Visual Studio, Azure Dev Ops
• Data Platforms & Engineering Tools: Snowflake,…