Data Engineer

Data Engineer

The Data Engineer is a mid-level individual contributor responsible for the systems and structures that make Hendrick Autoguard's data reliable, accessible, and useful. This role owns the design and operation of the ingestion pipelines, transformation logic, and data models that serve both business intelligence and AI initiatives.

This is not a role that waits for requirements to arrive fully formed. The Data Engineer is expected to develop a working understanding of how the business operates and to apply that knowledge when making technical decisions. A pipeline that runs on time but models the business incorrectly has not done its job. That distinction sits at the center of this role.

The role works alongside the analysts and BI developers who build reporting on the data platform, the data science and AI teams who use curated data for model development, and the team that administers the underlying cloud infrastructure. The Data Engineer makes sure the data layer serves each of these groups well, so that none of them has to rebuild it for their own use.

The Data Engineer owns the movement of data from source systems into the Snowflake data platform. In practice that means designing, building, and maintaining ingestion pipelines; orchestrating workflows in Dagster so they are observable, reliable, and operationally sound; and monitoring pipeline health and data availability. When a load fails or data arrives late, the Data Engineer investigates, fixes the underlying cause, and puts alerting in place so the same problem surfaces early next time rather than in a stakeholder's report.

Once data lands, the Data Engineer develops and maintains the dbt transformation models that turn raw source data into clean, tested, and well-documented datasets. That includes designing dimensional models and data marts that support both reporting and machine learning use cases, and implementing data quality checks and testing standards throughout the transformation layer. Downstream consumers should be able to trust a dataset without re-verifying it themselves.

The Data Engineer also prepares data for AI. That work includes structuring feature datasets and training data pipelines, and collaborating with data science and AI teams to make sure the data meets their requirements for quality, freshness, and structure. The Data Engineer contributes to the semantic layer that gives AI and analytics consumers consistent, well-defined access to business metrics and entities, and keeps data lineage and governance in view, since AI applications raise the stakes on knowing where data came from and how it may be used.

The Data Engineer is also expected to advise on the strategic direction of the data engineering toolset, weighing in on platform and feature updates and evaluating new capabilities as they become available. Staying current with best practices and industry advancements in data engineering, AI data preparation, and orchestration is part of the job, not a side interest, and that knowledge should inform how the team's tools and standards evolve over time.

Across all of this work, the Data Engineer builds working knowledge of the Autoguard business processes it supports, including vehicle service contract and protection product sales through dealership partners, claims administration, and cancellations, along with the workflows and decisions that depend on data from those areas. The Data Engineer engages directly with business stakeholders to understand their data needs, translates those needs into sound technical designs, and applies business context when weighing modeling decisions, pipeline priorities, and data quality standards. That knowledge makes each new request faster to scope. It also makes the Data Engineer a useful partner when a team is still working out which question it needs to answer.

Dashboard and report preparation are not a routine part of this role, and primary ownership of that work belongs to analysts and BI developers. The Data Engineer may occasionally need to support that function, though, whether by building or troubleshooting a report in a pinch or by helping an analyst work through a modeling issue at the source. The Data Engineer's core job is to deliver the modeled, tested data those teams build on, and to work with them when a reporting need exposes a gap in the data layer.

Experience And Qualifications

A candidate for this role has 3–7 years of professional experience in data engineering or a closely related discipline. They are proficient in SQL and have 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, as is familiarity with AWS, including storage, IAM, and basic networking concepts.

Preferred experience includes Python for pipeline development or data scripting; exposure to data quality frameworks, data contracts, or observability tooling; supporting ML pipelines or AI data preparation workflows; familiarity with medallion architecture or similar layered data design patterns; and involvement in data governance or data catalog efforts. The current technology environment includes Snowflake, Dagster, dbt, AWS (S3, EC2, and IAM), Python, and GitHub.

Candidates must be able to engage with non-technical stakeholders and translate business needs into technical requirements. Clear written and verbal communication is not optional in this role. The Data Engineer produces model documentation, dataset descriptions, and design notes that analysts, data scientists, and business stakeholders rely on. That documentation needs to be accurate, specific, and usable without a follow-up conversation.

The Data Engineer works on site at Hendrick Automotive Group headquarters in a standard office environment, collaborating in person with technology teams and the business stakeholders this role supports. Travel is minimal, and may be by car or plane. Position is not remote due to essential functions of the job. Position is required to sit for prolonged periods of time, extensive use of computer and related functions like typing and other office equipment used in regular performance of essential functions like phone, printer.

Hendrick is an Equal Opportunity employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply.