Data Engineer

At Hendrick Autoguard - HIC, this mid-level Data Engineer role helps turn operational data into dependable foundations for business intelligence and AI initiatives. You will design ingestion pipelines, transformation logic, and data models that improve data reliability, accessibility, and clarity across analytics and machine learning use cases.

Responsibilities

• Own the design and operation of ingestion pipelines, transformation logic, and data models that keep Hendrick Autoguard data reliable and usable.
• 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, investigate load failures or late data, and fix root causes.
• Implement alerting so recurring problems surface early rather than through delayed stakeholder reporting.
• Develop and maintain dbt transformation models that produce clean, tested, and well-documented datasets.
• Design dimensional models and data marts that support both reporting and machine learning.
• Embed data quality checks and testing standards throughout the transformation layer.
• Prepare data for AI by structuring feature datasets and building training data pipelines.
• Collaborate with data science and AI teams to ensure data meets requirements for quality, freshness, and structure.
• Contribute to the semantic layer so AI and analytics consumers access consistent, well-defined business metrics and entities.
• Maintain awareness of data lineage and governance, especially as AI applications increase the importance of understanding provenance and intended use.
• Advise on the strategic direction of data engineering tools, weighing platform and feature updates and evaluating new capabilities.
• Build knowledge of the Autoguard business processes supported by the data, including vehicle service contract and protection product sales through dealership partners, claims administration, and cancellations.
• Work with business stakeholders to understand data needs, translate them into technical designs, and apply business context to modeling decisions, pipeline priorities, and data quality standards.
• Occasionally support dashboard and report preparation by building or troubleshooting a report, or helping an analyst resolve a modeling issue at the source.

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 engage with non-technical stakeholders and translate business needs into technical requirements.
• Clear written and verbal communication is required.
• Ability to produce accurate, specific model documentation, dataset descriptions, and design notes that can be used without requiring a follow-up conversation.

Working Conditions

• Onsite work at Hendrick Automotive Group headquarters in Charlotte, NC, in a standard office environment with in-person collaboration.
• Minimal travel, potentially by car or plane.
• Not remote due to essential job functions.
• Required to sit for prolonged periods and use office equipment extensively, including typing and related computer tasks (phone, printer, and standard office tools).