Job description

Job Description The Role The Finance Data and Insights team in the Business Applications (Finance, Legal & SAP Engineering – FLSE) organization is responsible for empowering Finance and Legal teams by delivering reliable and secure AI-driven tools that streamline workflows, accelerate decision making, surface actionable insights, and unlock measurable productivity gains across the product lifecycle. As a Systems Engineer , you will be responsible for developing data intensive and AI-enabled data solutions and tools that support the Finance team. You will work with complex data requirements and deliver solutions using industry standard practices across SQL, Databricks and Python. You will design and build software and data solutions based on detailed requirements and system specifications, with a strong focus on data quality, performance, and reliability. You will help define patterns and best practices for SQL, Databricks (DBX), and AI/ML integrations within Business Applications and play a key role in ongoing modernization and cloud initiatives. You will also develop agents and solutions using Glean and Genie, driving transformation in ways of working through agents and automated workflows. What You’ll Do Design, develop, and maintain data-driven and AI-enabled data solutions and services that support Finance and Legal teams. Develop high-quality, performant SQL and PySpark code in Databricks for complex data transformations and analytical data modeling. Design, build, and optimize Databricks (DBX) data pipelines and workflows to support scalable batch and near real-time data processing.. Partner with data science and AI teams to productionize AI/ML and LLM-based solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement. Develop agents and automated workflows using Glean and Genie to transform Finance and Legal ways of working. Proactively identify and remediate issues related to patterns, performance, security, and data correctness. Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and Statement of Technical Direction. Troubleshoot and resolve production issues across the full stack (data, application, infrastructure), driving root cause analysis, stable fixes, and clear documentation. Document software and data solutions and ensure technical documentation meets GM standards and can be leveraged across FLSE and related business systems. Your Skills & Abilities (Required Qualifications) Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience. 2–5 years of systems engineering experience delivering data-intensive and analytics-focused solutions, with proven technical and professional skills in SQL, Python/PySpark , and cloud data platforms such as Databricks . Experience working with complex SQL queries and user-defined functions in Databricks , including performance tuning and optimization against large datasets Hands-on experience with AI agents and/or skills, such as: Building or configuring agents in platforms like Glean, Genie , or IDE-based agents ; and/or Authoring Markdown-based skill/rule files (e.g., SKILL.md, rules.md ) that guide AI behavior. Familiarity with Model Context Protocol (MCP) or similar patterns for connecting agents to tools, APIs, and data sources, with a strong interest in deepening expertise in this area. Comfort working with Markdown for technical documentation, skill definitions, and agent specifications.. Strong problem solving skills with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high-quality solutions. Excellent written and verbal communication skills with the ability to collaborate with both technical and non-technical stakeholders. Demonstrated ownership mindset, accountability for quality, and focus on delivering measurable value to internal customers. What Will Give You A Competitive Edge (Preferred Qualifications) Experience delivering enterprise-grade or global, scalable data-intensive or analytics-focused solutions and platforms. Deep hands-on experience with Databricks (Delta tables, notebooks, jobs, workflows) and/or Spark for data engineering, analytics, or AI workloads. Knowledge of relational and dimensional data modeling, data quality practices, metadata management, and data governance in an enterprise environment. Demonstrated experience designing and implementing agent and skill ecosystems, including: Defining and maintaining SKILL.md-style definitions and associated Markdown assets . Wiring agents to MCP servers and external tools in a secure, governed way. Applying version control, testing, and rollout patterns to agents and skills. Demonstrated ability to influence technical direction, establish reusable patterns and standards, and mentor less experienced engineers. Ability to manage multiple initiatives and priorities in a fast-paced environment while maintaining high engineering standards. 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., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. This job may be eligible for relocation benefits. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we re looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources . Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 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 . Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Requirements

Must-haves

What You’ll Do Design, develop, and maintain data-driven and AI-enabled data solutions and services that support Finance and Legal teams.
Develop high-quality, performant SQL and PySpark code in Databricks for complex data transformations and analytical data modeling.
Design, build, and optimize Databricks (DBX) data pipelines and workflows to support scalable batch and near real-time data processing..
Partner with data science and AI teams to productionize AI/ML and LLM-based solutions, including feature pipelines, inference integrations, monitoring, and continuous improvement.
Develop agents and automated workflows using Glean and Genie to transform Finance and Legal ways of working.
Proactively identify and remediate issues related to patterns, performance, security, and data correctness.
Lead or contribute to solution design, including architecture, patterns, and technology choices aligned with GM standards and Statement of Technical Direction.
Troubleshoot and resolve production issues across the full stack (data, application, infrastructure), driving root cause analysis, stable fixes, and clear documentation.
Document software and data solutions and ensure technical documentation meets GM standards and can be leveraged across FLSE and related business systems.
Your Skills & Abilities (Required Qualifications) Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Engineering, or a related field, OR equivalent experience.
2–5 years of systems engineering experience delivering data-intensive and analytics-focused solutions, with proven technical and professional skills in SQL, Python/PySpark , and cloud data platforms such as Databricks .
Experience working with complex SQL queries and user-defined functions in Databricks , including performance tuning and optimization against large datasets
Hands-on experience with AI agents and/or skills, such as: Building or configuring agents in platforms like Glean, Genie , or IDE-based agents ; and/or
Authoring Markdown-based skill/rule files (e.g., SKILL.md, rules.md ) that guide AI behavior.
Familiarity with Model Context Protocol (MCP) or similar patterns for connecting agents to tools, APIs, and data sources, with a strong interest in deepening expertise in this area.
Comfort working with Markdown for technical documentation, skill definitions, and agent specifications..
Strong problem solving skills with the ability to break down complex technical and data challenges into clear, actionable steps and deliver high-quality solutions.
Excellent written and verbal communication skills with the ability to collaborate with both technical and non-technical stakeholders.
Demonstrated ownership mindset, accountability for quality, and focus on delivering measurable value to internal customers.
Deep hands-on experience with Databricks (Delta tables, notebooks, jobs, workflows) and/or Spark for data engineering, analytics, or AI workloads.
Knowledge of relational and dimensional data modeling, data quality practices, metadata management, and data governance in an enterprise environment.
Demonstrated experience designing and implementing agent and skill ecosystems, including: Defining and maintaining SKILL.md-style definitions and associated Markdown assets .
Wiring agents to MCP servers and external tools in a secure, governed way.

Nice-to-haves

What Will Give You A Competitive Edge (Preferred Qualifications) Experience delivering enterprise-grade or global, scalable data-intensive or analytics-focused solutions and platforms.

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Keywords to mirror

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Platform: workday
Effort: long

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