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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 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.
Job Responsibility:
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 have:
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