On-site Data Engineer

Requirements:

• 3–7 years of professional experience in data engineering or a closely related field.
• Proficiency in SQL and hands-on experience with a cloud data warehouse, a data transformation and modeling framework, and a workflow orchestration tool.
• Experience with Snowflake, dbt, and Dagster is strongly preferred; familiarity with AWS, including storage, IAM, and basic networking concepts, is also preferred.
• Preferred experience includes Python for pipeline development or data scripting; data quality frameworks, data contracts, or observability tools; support for ML pipelines or AI data preparation; medallion architecture or similar layered design patterns; and data governance or catalog initiatives.
• Ability to work with non-technical stakeholders and translate business needs into technical requirements.
• Strong written and verbal communication skills, including the ability to produce accurate, specific, and usable model documentation, dataset descriptions, and design notes.
• Our current technology environment includes Snowflake, Dagster, dbt, AWS (S3, EC2, and IAM), Python, and GitHub.

Responsibilities:

• Design, build, and maintain data ingestion pipelines that move data from source systems into our Snowflake platform.
• Orchestrate workflows in Dagster, monitor pipeline health and data availability, investigate failures or delays, resolve underlying causes, and implement alerting.
• Develop and maintain dbt transformation models that create clean, tested, and documented datasets.
• Design dimensional models and data marts for reporting and machine learning, and implement data quality checks and testing standards.
• Prepare feature datasets and training-data pipelines, collaborating with data science and AI teams on data quality, freshness, and structure.
• Contribute to a semantic layer that provides consistent access to business metrics and entities, while maintaining awareness of data lineage and governance.
• Advise on the direction of our data engineering tools, assess platform updates and new capabilities, and apply current practices and industry developments to our tools and standards.
• Build knowledge of the business processes we support, including vehicle service contract and protection product sales through dealership partners, claims administration, and cancellations.
• Engage with business stakeholders to understand data needs, translate them into technical designs, and use business context to guide modeling decisions, pipeline priorities, and data quality standards.
• Occasionally support dashboard or report work, troubleshoot reporting issues, or help analysts resolve modeling problems at the source; our primary focus for this role is delivering the modeled, tested data those teams use.

Technologies:

• AI
• AWS
• Cloud
• Data Warehouse
• EC2
• GitHub
• IAM
• Support
• Machine Learning
• Python
• SQL
• Snowflake
• dbt
• Business Intelligence

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We are hiring a mid-level individual-contributor Data Engineer for Hendrick Autoguard, based at Hendrick Automotive Group headquarters at 6030 East Independence Blvd, Charlotte, North Carolina 28212. The role works closely with analysts, BI developers, data science and AI teams, cloud infrastructure colleagues, and business stakeholders to provide a reliable, accessible data foundation for analytics and AI initiatives. This is an on-site position in a standard office environment and is not remote because of the roles essential functions. Travel is minimal and may involve car or plane. The work requires prolonged sitting and extensive computer use, including typing and use of standard office equipment. We are an equal opportunity employer and encourage minorities, women, veterans, and individuals with disabilities to apply.

last updated 43 week of 2026