Data Engineer

Hendrick Autoguard - HIC; Charlotte (NC); On-site; USD 110,000 - 150,000; Full time

Job summary

Hendrick Autoguard in Charlotte, NC is seeking a data engineer to design and operate ingestion pipelines, transformations, and data models for BI and AI initiatives, onsite at our Charlotte campus. You will build Snowflake-based pipelines with dbt and Dagster, ensure data quality, governance, and observability, and collaborate with data science teams to prepare datasets for analytics and machine learning.

The role emphasizes reliability, documentation, and stakeholder collaboration across

Qualifications

• 3–7 years of professional experience in data engineering or a closely related discipline.
• Strong proficiency in SQL
• Hands-on experience with a cloud data warehouse, a data transformation and modeling framework, and a workflow orchestration tool
• Snowflake, dbt, and Dagster experience (strongly preferred)
• Familiarity with AWS, including storage, IAM, and basic networking concepts
• Preferred: Python experience 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 design patterns
• Preferred: involvement in data governance or data catalog efforts
• Able to engage with non-technical stakeholders and translate business needs into technical requirements
• Clear written and verbal communication skills
• Ability to produce accurate, specific model documentation, dataset descriptions, and design notes that do not require follow-up conversation

Responsibilities

• Own design and operation of ingestion pipelines, transformations, and data models to keep Hendrick Autoguard data reliable, accessible, and usable
• Build ingestion pipelines that move data into the Snowflake data platform
• Orchestrate data workflows with Dagster with emphasis on observability and reliability
• Monitor pipeline health and data availability; investigate load failures and root causes
• Implement alerting to detect issues early
• Develop and maintain dbt transformation models with clean, tested datasets
• Create dimensional models and data marts for reporting and ML use cases
• Apply data quality checks across the transformation layer
• Prepare data for AI by structuring feature datasets and training pipelines
• Collaborate with data science/AI teams to ensure dataset quality and structure
• Contribute to the semantic layer for consistent access to metrics
• Maintain data lineage and governance visibility, especially for AI use cases
• Advise on the strategic direction of data engineering tools and platforms
• Stay current with best practices to evolve team tools and standards
• Understand Autoguard business processes supported by data (contracts, sales, claims)
• Translate business needs into technical designs with stakeholders
• Support dashboards/reports by assisting analysts with modeling issues

Skills

SQL

Data modeling

ETL development

Stakeholder comms

Python

Observability tooling

Tools

Snowflake

dbt

Dagster

AWS

S3

EC2

IAM

GitHub

Job description

Charlotte, NC onsite role focused on building reliable ingestion, transformations, and data models for BI and AI initiatives.

Responsibilities

• Own the design and ongoing operation of ingestion pipelines, transformation logic, and data models to keep Hendrick Autoguard data reliable, accessible, and usable
• Design, build, and maintain ingestion pipelines that move data from source systems into the Snowflake data platform
• Orchestrate data workflows in Dagster with an emphasis on observability, reliability, and operational soundness
• Monitor pipeline health and data availability, investigate load failures or late-arriving data, and fix root causes
• Implement alerting so issues are detected early rather than discovered through downstream reports
• Develop and maintain dbt transformation models that produce clean, tested, well-documented datasets
• Create dimensional models and data marts to support reporting and machine learning use cases
• Apply data quality checks and testing standards throughout the transformation layer
• Prepare data for AI by structuring feature datasets and building training data pipelines
• Partner with data science and AI teams to ensure datasets meet quality, freshness, and structure requirements
• Contribute to the semantic layer to provide consistent, well-defined access to business metrics and entities for analytics and AI consumers
• Maintain visibility into data lineage and governance needs, especially for AI use cases where provenance matters
• Advise on the strategic direction of the data engineering toolset, including platform and feature updates and evaluation of new capabilities
• Stay current with best practices in data engineering, AI data preparation, and orchestration and use that knowledge to evolve team tools and standards
• Build working knowledge of 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 and pipeline priorities
• Occasionally support dashboard and report preparation by building or troubleshooting a report or assisting analysts with source-side modeling issues

Requirements

• 3–7 years of professional experience in data engineering or a closely related discipline
• Strong proficiency in SQL
• Hands-on experience with a cloud data warehouse, a data transformation and modeling framework, and a workflow orchestration tool
• Snowflake, dbt, and Dagster experience (strongly preferred)
• Familiarity with AWS, including storage, IAM, and basic networking concepts
• Preferred: Python experience 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 design patterns
• Preferred: involvement in data governance or data catalog efforts
• Able to engage with non-technical stakeholders and translate business needs into technical requirements
• Clear written and verbal communication skills
• Ability to produce accurate, specific model documentation, dataset descriptions, and design notes that do not require follow-up conversation

Technologies

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

Working Conditions

• Onsite at Hendrick Automotive Group headquarters in a standard office environment with in-person collaboration
• Minimal travel; may be by car or plane
• Not remote due to essential functions of the job
• Requires sitting for prolonged periods and extensive use of computer and office equipment (typing, phone, printer)