Staff Data Engineer – Telematics Data Products
General Motors
Staff Data Engineer – Telematics Data Products
Job Description
Job DescriptionThis role is categorized as hybrid. This means the successful candidate is expected to report to Warren Global Technical Center or Austin Technical Center three times per week, at minimum [or other frequency dictated by the business if more than 3 days].The RoleWe're looking for a hands-on Staff Data Engineer to build the next generation of telematics data products that power analytics, AI, and decision-making across the enterprise.This role sits at the intersection of data architecture, analytics, and platform engineering. Success isn't measured by pipelines alone—it's about creating trusted, reusable, analytics-ready data products that make complex telemetry data easier to discover, understand, and use at scale.You'll help define the foundational datasets, shared metrics, and curated data products that enable teams across engineering, product, quality, safety, and operations to unlock value from connected vehicle data.What You'll DoDesign and build reusable telematics data products that make analytics faster, simpler, and more scalable across the enterpriseDesign canonical data products that make telematics data easier to understand, join, and reuseBuild curated analytics-ready datasets that standardize metrics, aggregations, and business logic across teamsTurn repeated analytical work into scalable, reusable data productsUse data usage patterns and adoption signals to help prioritize the data product roadmapDesign and implement scalable solutions in Azure DatabricksImprove performance, scalability, reliability, and cost efficiencyEnable self-service analytics by making data easier to discover, trust, and consumeBuild data products that support analytics, machine learning, and AI use casesThis is an opportunity to help define how a large-scale telematics platform supports analytics, AI, and enterprise decision-making.The data products you build will help teams answer questions such as:How many miles were driven with Super Cruise last week?Which vehicle signals are most correlated with battery-related warranty events?How are connected services performing across vehicle programs?What emerging trends are appearing across EV systems, charging, and battery health?Which ADAS and safety systems are generating the highest diagnostic or service activity?Where should the next wave of EV charging infrastructure be deployed?How can telemetry data improve product quality, warranty performance, and future vehicle development?You'll help move the organization from custom analytics and duplicated logic toward trusted, reusable data products that scale across the enterprise.Your Skills & Abilities (Required Qualifications) Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field8+ years of experience in data engineering or analytics platforms, including experience operating at a senior or staff level with responsibility for architecture, technical direction, and cross-team impactDeep hands-on experience with DatabricksStrong data modeling, semantic design, and data architecture skillsExpertise in SQL, Spark, and distributed data processingExperience designing solutions for performance, scalability, reliability, and cost optimizationStrong understanding of how analysts, engineers, data scientists, and ML practitioners consume dataExperience working with IoT, telemetry, event-stream, or sensor dataExperience enabling AI, machine learning, and advanced analytics through governed and reusable data productsBuilder mindset with strong technical judgment and a bias toward simplificationWhat Can Give You a Competitive Advantage (Preferred Qualifications)Master's degree in Computer Science, Data Engineering, Data Science, Analytics, or a related disciplineAbility to think deeply about:How data should be modeledHow analytics should workHow reusable data products should be designedHow platform capabilities can reduce duplication and wasted effortHow usage patterns should drive future investmentsThis job may be eligible for relocation benefits.Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.Compensation: The expected base compensation for this role is: $160,200 - $211,950. 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.)#LI-CC1
About GMOur 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 OverviewFrom 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.AccommodationsGeneral 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.
Locations
- United States of America, Texas, Austin
- United States of America, Michigan, Warren
Salary
160,200 - 211,950 USD / yearly
Skills Required
- data engineeringintermediate
- Databricksintermediate
- SQLintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field (degree in computer science)
- 8+ years of experience in data engineering or analytics platforms, including experience operating at a senior or staff level with responsibility for architecture, technical direction, and cross-team impact (experience, 8 years)
- Deep hands-on experience with Databricks (experience)
- Strong data modeling, semantic design, and data architecture skills (experience)
- Expertise in SQL, Spark, and distributed data processing (experience)
- Experience designing solutions for performance, scalability, reliability, and cost optimization (experience)
- Strong understanding of how analysts, engineers, data scientists, and ML practitioners consume data (experience)
- Experience working with IoT, telemetry, event-stream, or sensor data (experience)
- Experience enabling AI, machine learning, and advanced analytics through governed and reusable data products (experience)
- Builder mindset with strong technical judgment and a bias toward simplification (experience)
- Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Mathematics, Statistics, or a related technical field (degree in computer science)
- 8+ years of experience in data engineering or analytics platforms, including experience operating at a senior or staff level with responsibility for architecture, technical direction, and cross-team impact (experience, 8 years)
- Deep hands-on experience with Databricks (experience)
- Strong data modeling, semantic design, and data architecture skills (experience)
- Expertise in SQL, Spark, and distributed data processing (experience)
- Experience designing solutions for performance, scalability, reliability, and cost optimization (experience)
- Strong understanding of how analysts, engineers, data scientists, and ML practitioners consume data (experience)
- Experience working with IoT, telemetry, event-stream, or sensor data (experience)
- Experience enabling AI, machine learning, and advanced analytics through governed and reusable data products (experience)
- Builder mindset with strong technical judgment and a bias toward simplification (experience)
Preferred Qualifications
- Master's degree in Computer Science, Data Engineering, Data Science, Analytics, or a related discipline (degree in computer science)
- Ability to think deeply about: (experience)
- How data should be modeled (experience)
- How analytics should work (experience)
- How reusable data products should be designed (experience)
- How platform capabilities can reduce duplication and wasted effort (experience)
- How usage patterns should drive future investments (experience)
- Master's degree in Computer Science, Data Engineering, Data Science, Analytics, or a related discipline (degree in computer science)
- Ability to think deeply about: (experience)
- How data should be modeled (experience)
- How analytics should work (experience)
- How reusable data products should be designed (experience)
- How platform capabilities can reduce duplication and wasted effort (experience)
- How usage patterns should drive future investments (experience)
Responsibilities
- Design and build reusable telematics data products that make analytics faster, simpler, and more scalable across the enterprise
- Design canonical data products that make telematics data easier to understand, join, and reuse
- Build curated analytics-ready datasets that standardize metrics, aggregations, and business logic across teams
- Turn repeated analytical work into scalable, reusable data products
- Use data usage patterns and adoption signals to help prioritize the data product roadmap
- Design and implement scalable solutions in Azure Databricks
- Improve performance, scalability, reliability, and cost efficiency
- Enable self-service analytics by making data easier to discover, trust, and consume
- Build data products that support analytics, machine learning, and AI use cases
- Design and build reusable telematics data products that make analytics faster, simpler, and more scalable across the enterprise
- Design canonical data products that make telematics data easier to understand, join, and reuse
- Build curated analytics-ready datasets that standardize metrics, aggregations, and business logic across teams
- Turn repeated analytical work into scalable, reusable data products
- Use data usage patterns and adoption signals to help prioritize the data product roadmap
- Design and implement scalable solutions in Azure Databricks
- Improve performance, scalability, reliability, and cost efficiency
- Enable self-service analytics by making data easier to discover, trust, and consume
- Build data products that support analytics, machine learning, and AI use cases
- This is an opportunity to help define how a large-scale telematics platform supports analytics, AI, and enterprise decision-making.The data products you build will help teams answer questions such as:
- How many miles were driven with Super Cruise last week?
- Which vehicle signals are most correlated with battery-related warranty events?
- How are connected services performing across vehicle programs?
- What emerging trends are appearing across EV systems, charging, and battery health?
- Which ADAS and safety systems are generating the highest diagnostic or service activity?
- Where should the next wave of EV charging infrastructure be deployed?
- How can telemetry data improve product quality, warranty performance, and future vehicle development?
- How many miles were driven with Super Cruise last week?
- Which vehicle signals are most correlated with battery-related warranty events?
- How are connected services performing across vehicle programs?
- What emerging trends are appearing across EV systems, charging, and battery health?
- Which ADAS and safety systems are generating the highest diagnostic or service activity?
- Where should the next wave of EV charging infrastructure be deployed?
- How can telemetry data improve product quality, warranty performance, and future vehicle development?
- You'll help move the organization from custom analytics and duplicated logic toward trusted, reusable data products that scale across the enterprise.
Benefits
- general: Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
- general: The expected base compensation for this role is: $160,200 - $211,950. Actual base compensation within the identified range will vary based on factors relevant to the position.
- general: Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
- general: 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.
- general: 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.)
- general: 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.
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