Senior Quality Data and AI Engineer

Description
This role is categorized as hybrid. This means the successful candidate is expected to report to Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].
The Role
The Quality & Safety Data Platform team builds the governed data products behind GM quality, warranty, dealer, and vehicle analytics. We're seeking a Senior Quality Data & AI Engineer to design and operate reliable data platforms while helping build user-facing applications that make data accessible and actionable. Has demonstrated experience applying AI and machine-learning techniques to data engineering, such as integrating AI models or services into data pipelines and production applications. This role combines strong data engineering fundamentals with hands-on experience developing front-end applications in React. You'll partner with product, analytics, and engineering teams to deliver end-to-end solutions-from ingestion and transformation through APIs and intuitive interfaces.
What You'll Do

• Develop and productionize reliable batch and streaming data products in Azure Databricks, using Spark Declarative Pipelines, Delta Lake, Unity Catalog, and Bronze, Silver, and Gold patterns that quality, warranty, and AI applications can trust.
• Identify opportunities to apply AI across data workflows and deliver solutions that improve efficiency, quality, or decision-making.
• Build and maintain data services and APIs that securely expose trusted, well-documented data to applications.
• Develop responsive front-end features using React, JavaScript or TypeScript, and modern web development practices.
• Collaborate with product designers and stakeholders to translate workflows and data needs into clear, usable interfaces.
• Establish data quality checks, observability, lineage, and alerting; investigate and resolve pipeline and application issues.
• Improve performance, reliability, security, and cost efficiency across data and application systems.
• Apply engineering best practices, including code review, automated testing, CI/CD, workload identity, security, cost, observability, and production support, and gate agent releases with evaluation of task success, tool use, grounding, latency, and cost.
• Mentor engineers, provide technical guidance, and contribute to roadmaps and architectural decisions.

Your Skills & Abilities (Required Qualifications)

• 5+ years of professional experience in data engineering, software engineering, or a closely related field.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent experience.
• Strong proficiency in SQL, Python, PySpark and a programming language used for data engineering, such as Scala, or Java.
• Experience designing production-grade ETL/ELT pipelines and working with data warehouses, data lakes, or lakehouse platforms.
• Practical experience using AI tools and services to improve data engineering workflows, with an understanding of responsible and secure AI use
• Hands-on experience building or maintaining front-end applications with React; familiarity with component-based UI patterns.
• Experience integrating front-end applications with REST or similar APIs and handling asynchronous data states, errors, and loading behavior.
• Understanding of data modeling, schema evolution, data quality, and distributed processing concepts.
• Strong experience with Databricks on a cloud platform, building and supporting scalable data pipelines
• Strong communication and problem-solving skills, with the ability to work across technical and nontechnical teams.

What Can Give You a Competitive Advantage (Preferred Qualifications)

• Experience with tools such as Apache Spark, Kafka, Airflow, or comparable technologies.
• Experience with cloud data platforms such as Snowflake, BigQuery, Redshift, or comparable services.
• Familiarity with Docker, Kubernetes, infrastructure as code, and cloud-native architectures.
• Experience with front-end testing tools, accessibility practices, and design systems.
• Experience implementing authentication, authorization, and secure handling of sensitive data.
• A track record of mentoring teammates and leading delivery across multiple systems or teams.

This job may be eligible for relocation benefits.
Compensation:

• The expected base compensation for this role is: $125,000 - $168,650. Actual base compensation within the identified range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)
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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.
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