Data Engineer

Hendrick Autoguard - HIC is looking for a mid-level Data Engineer to help design and run ingestion pipelines, transformation logic, and data models that keep data reliable and usable. This onsite role in Charlotte, NC focuses on operationally sound data workflows using Dagster, dbt-based transformations with testing and documentation, and data preparation that supports both business intelligence and AI initiatives.

Responsibilities

• Own the design and operation of ingestion pipelines, transformation logic, and data models that make Hendrick Autoguard data reliable, accessible, and useful.
• Design, build, and maintain ingestion pipelines that move data from source systems into the Snowflake data platform.
• Orchestrate workflows in Dagster with an emphasis on observability, reliability, and operational soundness.
• Monitor pipeline health and data availability, investigating load failures or late data and correcting root causes.
• Implement alerting to surface issues early rather than after results reach stakeholders.
• Develop and maintain dbt transformation models that produce clean datasets with testing and documentation.
• Design dimensional models and data marts supporting both reporting and machine learning use cases.
• Implement data quality checks and testing standards across the transformation layer.
• Prepare data for AI by structuring feature datasets and training data pipelines.
• Collaborate with data science and AI teams to ensure data quality, freshness, and structure meet their needs.
• Contribute to the semantic layer so AI and analytics consumers have consistent, well-defined access to business metrics and entities.
• Keep data lineage and governance in view, recognizing that AI increases the importance of understanding data origin and usage.
• Advise on the strategic direction of the data engineering toolset, weighing in on platform and feature updates and evaluating new capabilities.
• Stay current with best practices and industry advancements in data engineering, AI data preparation, and orchestration, and apply that knowledge to evolving team standards.
• Build working knowledge of Autoguard business processes, including vehicle service contract and protection product sales through dealership partners, claims administration, and cancellations, plus related workflows and decisions.
• Engage with business stakeholders to understand data needs, translate them into technical designs, and apply business context when making modeling, prioritization, and data quality decisions.
• Occasionally support dashboard and report preparation by building or troubleshooting a report, or helping an analyst work through a source modeling issue.

Requirements

• 3–7 years of professional experience in data engineering or a closely related discipline.
• Proficient in SQL.
• 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 (strongly preferred).
• Familiarity with AWS, including storage, IAM, and basic networking concepts.
• Preferred: Python for pipeline development or data scripting.
• Preferred: exposure to data quality frameworks, data contracts, or observability tooling.
• Preferred: experience supporting ML pipelines or AI data preparation workflows.
• Preferred: familiarity with medallion architecture or similar layered data design patterns.
• Preferred: involvement in data governance or data catalog efforts.
• Ability to work with non-technical stakeholders and translate business needs into technical requirements.
• Clear written and verbal communication.
• Ability to produce accurate, specific, and usable model documentation, dataset descriptions, and design notes without requiring follow-up conversations.

Technologies

• Snowflake
• dbt
• Dagster
• AWS
• S3
• EC2
• IAM
• Python
• GitHub
• SQL

Working Conditions

• Onsite work at Hendrick Automotive Group headquarters in a standard office environment with in-person collaboration with technology teams and business stakeholders.
• Minimal travel, potentially by car or plane.
• Not remote due to essential functions of the job.
• Required to sit for prolonged periods of time and use office equipment extensively, including typing and related functions.