Snowflake Data Engineer

Lithia & Driveway

9d•$80,000 - $115,000•Remote

About The Position

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.

Requirements

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 DevOps Data Platforms & Engineering Tools: Snowflake, Databricks, and DBT
Proficiency in Snowflake development, including stored procedures, UDFs, query performance tuning, and Snowpipe configuration.
Strong SQL development skills, including query optimization and stored procedure design.
Solid understanding of ETL/ELT processes, data integration patterns, and foundational data warehouse concepts.
Experience supporting and troubleshooting data integrations across cross-functional teams.
Proficiency with version control systems such as Git or TFS.
Knowledge of CI/CD pipelines and best practices for data engineering projects.
Strong attention to detail with the ability to manage multiple priorities and deadlines effectively.
Excellent communication and collaboration skills.
1+ year of experience in analytics or data engineering, working closely with cross-functional teams.
2+ years of experience in SQL Server development or equivalent SQL-based data engineering environments.
High School graduate or equivalent, 18 years or older required.
We are a drug free workplace.

Responsibilities

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