Data Engineer

Position: Staff Data Engineer
# Staff Data Engineer## General Motors Published 28 Mar 2026## Role Highlights### Languages used

Python

JavaC++SQL### Key skills

Data Science Data Engineer Data Architect Data Infrastructure Data Governance Computer Science

Integrations

API Product Management Information Systems Distributed Systems Data Processing System Design Data Quality

AIMachine Learning Operations Security UIData Sets Transformation Logging Mathematics Cloud Architecture LLMs Automation Search ### Tools, Libraries and Frameworks Data Bricks Airflow Snow Flake Kafka Azure AWSGCPAD## Description  

Job Description    

The Role  As a Staff Data Engineer within the Marketing Applied Sciences organization, you will be responsible for designing and developing high-quality, well-managed, and reusable data and analytics products (including AI/ML, Data, and Marketing solutions) for applied analytics solutions and insights. You will design, build, and optimize data engineering pipelines and marketing data products, as well as contribute to AI agents, LLM-based solutions, and Ad Ops pipelines, while owning and enforcing data and AI standards and ensuring security and compliance.

Additionally, the Data Engineer will contribute to building and maintaining LLM-based AI agents using both platform-native capabilities and custom agent frameworks, integrating them with enterprise-scale AI models and data systems. Agents will include wrappers and UI to seamlessly integrate sub agents. You will also be responsible for monitoring, maintaining, and enhancing data and ML pipelines and associated agents. This role will also be responsible for integrating with 3rd party data providers and marketing platforms, APIs, and providing marketing insights.

As a Staff Data Engineer you will collaborate closely with product managers, data engineers, data scientists, and other partners to develop state-of-the-art AI and Data Engineering solutions that enable the future of marketing.

Success in this role requires a blend of technical aptitude, marketing know-how, and cross-functional collaboration. This role is ideal for someone who thrives at the intersection of data engineering, data science, and marketing strategy, and who is eager to shape the future of customer experiences at one of the worlds most iconic automotive brands.  

What Youll Do   + Define, own, and enforce data and AI/ML standards and industry best practices and dedicate efforts to mentoring and overseeing AI/ML efforts across the Marketing Applied Sciences portfolio + Build and maintain scalable data pipelines, services, and AI agents to accelerate and optimize business processes and tooling + Identify and implement optimizations that improve the runtime, performance,scalability, stability, and cost efficiency of data platforms, pipelines, and AI/ML agents and workflows + Own data stewardship for key marketing datasets, driving data quality, documentation, access controls, and responsible use in partnership with data governance, privacy, and marketing stakeholders.

+ Help design and evolve marketing and Ad Ops data infrastructure, including privacy-safe environments such as data clean rooms, to enable advanced audience insights, activation, and measurement. + Design and implement robust data models, ingestion, and transformation workflows that ensure high-quality, well-documented, and discoverable data for analytics and AI use cases. + Collaborate with the Engineering community to highlight best practices, implement tactics, and provide feedback to the community + Build unit and integration tests, data quality checks, logging and observability, and all industry-standard best practices to ensure products are production ready + Elevate data and system design, diagnostics, and operational excellence to higher standards  Your Skills & Abilities (Required Qualifications)   + Bachelors degree in Computer Science, ML Engineering, Data Engineering, Information Systems, Mathematics, or a related technical field.

+ 8+ years of experience in Software Engineering, Data Engineering, Data Science or related field, building, maintaining and optimizing distributed systems + Experience building high performance data and AI solutions + Experience in Python and/or other Object-Oriented programming languages (Java, C++ etc.) + Proficiency in SQL and distributed data processing frameworks such as PySpark + Proficient with modern data platforms and tools such as Databricks, Airflow, dbt, Snowflake, Kafka, or similar + Proficient with cloud architecture systems such as Azure, AWS, GCP, etc.

+ Ability to communicate complex solutions with fellow Engineers and non-technical business stakeholders alike + Demonstrated ability to lead projects that bridge marketing, data science, and technology to drive measurable outcomes + Strong understanding of modern data architectures and pipelines, and familiarity with LLMs, AI agents, automation, and related best practices + Demonstrated success in collaborating with cross-functional teams and…