Data Engineering Enablement Consultant
About the position
This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI or Austin, TX three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role System Engineers are responsible for partitioning and allocating product, feature and system functionality to implementation teams. Safety, reliability, and regulatory compliance are factors considered in system design with the goal of optimizing performance, design, testability, and deployability. System engineers identify use cases, define functional technical requirements, enable robust implementation designs, and ensure built-in quality with test definition and traceability. Serve as primary point of contact for data domain and engineering inquiries. Provide first-level support and triage for all data-related issues including Databricks onboarding and configuration requests. The consultant will focus on consultation, enablement, and continuous improvement . They will work closely with data/software engineers, data scientists, architects, business, analysts, governance teams, and platform teams to improve customer experience, reduce escalations, and streamline the path to value on our platforms.
Responsibilities
• Serve as primary point of contact for data domain and engineering inquiries, acting as a central knowledge hub and ensuring easy access to information.
• Provide first-level support and triage for all data-related issues including Databricks onboarding and configuration changes.
• Assist customers with data domain and engineering-related inquiries and process optimizations across GM’s data landscape.
• Guide teams on best practices, platform capabilities, and strategic recommendations across the Data ecosystem.
• Work proactively to reduce escalations and response times , improving overall customer experience.
• Maintain and continuously improve documentation, runbooks, FAQs, processes, and tools related to the Data ecosystem.
• Identify gaps in knowledge and process and codify artifacts that reduce repeat inquiries and improve self-service capabilities.
• Analyze customer inquiries and feedback to identify trends, pain points, and opportunities to improve both customer experience and platform adoption.
• Partner with platform and engineering teams to improve processes, technology stack, and documentation in order to reduce inbound inquiries and overall support demand.
• Collaborate with platform owners, governance, security, and engineering teams to ensure aligned guidance and consistent messaging across the Data ecosystem.
• Support measurement of customer satisfaction, inquiry response times, and demand trends , and use these insights to drive continuous improvement in services and processes.
• Contribute to a culture of excellence and responsiveness through continuous improvement, collaboration, and knowledge sharing.
• Partner closely with cross-functional teams to translate technical and business requirements into robust, efficient solutions.
• Participate in code reviews, promote best practices, and mentor engineers to raise engineering quality across the team.
• Optimize storage and compute resources for performance and cost efficiency.
Requirements
• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related discipline.
• 5+ years of experience in data engineering, data platforms, analytics engineering, or related technical roles with significant exposure to modern cloud data platforms.
• Experience with Databricks platform.
• Proven cloud experience and strong familiarity with at least one cloud platform (Microsoft Azure - preferred, AWS, GCP).
• Demonstrated ability to consult with technical and non-technical stakeholders , translating complex platform concepts into clear, actionable guidance.
• Strong skills in collaboration and written and verbal communication , including documentation, FAQs, and customer-facing enablement materials.
• Proven track record of identifying process or documentation gaps and driving improvements that reduce operational friction and repeat inquiries.
• Experience with CI/CD pipelines and modern DevOps practices (e.g., GitHub, Terraform).
Nice-to-haves
• Experience serving in a platform, advisory, or consulting capacity supporting large-scale data or analytics platforms.
• Familiarity with GM data governance, security, and compliance practices , including how they apply to Cloud Data Platforms.
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.
Apply tot his job
Apply To this Job
This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI or Austin, TX three times per week, at minimum [or other frequency dictated by the business if more than 3 days]. The Role System Engineers are responsible for partitioning and allocating product, feature and system functionality to implementation teams. Safety, reliability, and regulatory compliance are factors considered in system design with the goal of optimizing performance, design, testability, and deployability. System engineers identify use cases, define functional technical requirements, enable robust implementation designs, and ensure built-in quality with test definition and traceability. Serve as primary point of contact for data domain and engineering inquiries. Provide first-level support and triage for all data-related issues including Databricks onboarding and configuration requests. The consultant will focus on consultation, enablement, and continuous improvement . They will work closely with data/software engineers, data scientists, architects, business, analysts, governance teams, and platform teams to improve customer experience, reduce escalations, and streamline the path to value on our platforms.
Responsibilities
• Serve as primary point of contact for data domain and engineering inquiries, acting as a central knowledge hub and ensuring easy access to information.
• Provide first-level support and triage for all data-related issues including Databricks onboarding and configuration changes.
• Assist customers with data domain and engineering-related inquiries and process optimizations across GM’s data landscape.
• Guide teams on best practices, platform capabilities, and strategic recommendations across the Data ecosystem.
• Work proactively to reduce escalations and response times , improving overall customer experience.
• Maintain and continuously improve documentation, runbooks, FAQs, processes, and tools related to the Data ecosystem.
• Identify gaps in knowledge and process and codify artifacts that reduce repeat inquiries and improve self-service capabilities.
• Analyze customer inquiries and feedback to identify trends, pain points, and opportunities to improve both customer experience and platform adoption.
• Partner with platform and engineering teams to improve processes, technology stack, and documentation in order to reduce inbound inquiries and overall support demand.
• Collaborate with platform owners, governance, security, and engineering teams to ensure aligned guidance and consistent messaging across the Data ecosystem.
• Support measurement of customer satisfaction, inquiry response times, and demand trends , and use these insights to drive continuous improvement in services and processes.
• Contribute to a culture of excellence and responsiveness through continuous improvement, collaboration, and knowledge sharing.
• Partner closely with cross-functional teams to translate technical and business requirements into robust, efficient solutions.
• Participate in code reviews, promote best practices, and mentor engineers to raise engineering quality across the team.
• Optimize storage and compute resources for performance and cost efficiency.
Requirements
• Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related discipline.
• 5+ years of experience in data engineering, data platforms, analytics engineering, or related technical roles with significant exposure to modern cloud data platforms.
• Experience with Databricks platform.
• Proven cloud experience and strong familiarity with at least one cloud platform (Microsoft Azure - preferred, AWS, GCP).
• Demonstrated ability to consult with technical and non-technical stakeholders , translating complex platform concepts into clear, actionable guidance.
• Strong skills in collaboration and written and verbal communication , including documentation, FAQs, and customer-facing enablement materials.
• Proven track record of identifying process or documentation gaps and driving improvements that reduce operational friction and repeat inquiries.
• Experience with CI/CD pipelines and modern DevOps practices (e.g., GitHub, Terraform).
Nice-to-haves
• Experience serving in a platform, advisory, or consulting capacity supporting large-scale data or analytics platforms.
• Familiarity with GM data governance, security, and compliance practices , including how they apply to Cloud Data Platforms.
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.
Apply tot his job
Apply To this Job