✦ Luna Orbit — Data & Analytics

Staff Data Engineer

at General Motors (GM)

📍 Remote, US Remote 💰 $160K – $246K USD / year Posted March 28, 2026
Salary $160K – $246K USD / year
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category Data & Analytics

This role involves designing and maintaining data pipelines and developing AI/ML solutions for marketing analytics, leveraging cloud platforms and ensuring data security.

  • Design data pipelines
  • Develop AI/ML solutions
  • Manage data governance
  • Collaborate with product teams
  • Optimize data workflows

Focuses on data engineering, AI/ML model development, data management, and integration of AI agents with marketing data, using Python, SQL, and cloud services.

The ideal candidate is a mid-level data engineer with experience designing data pipelines and developing AI/ML solutions, familiar with marketing data and cloud platforms, eager to work on innovative AI-driven analytics products.

Designing data pipelinesBuilding AI/ML solutionsData managementCollaborating with product teams
LLM-based solutionsAI agent developmentMarketing data productsData securityData optimization
PythonSQLCloud platformsAI/ML frameworks
Data pipelinesAI/MLdata engineeringdata productsAPIsdata governancePythonSQLcloud platformsAI standards
Data engineeringAI/MLData pipelinesData modelsAPIsData governancePythonSQLCloud platformsAI standards
CollaborationTechnical aptitudeMarketing know-howCross-functional teamworkProblem-solvingCommunication

Preferred

Data engineering certificationsAI/ML certifications
Industry Automotive / Marketing
Job Function Build and maintain data infrastructure for marketing analytics
Role Subtype Data & Analytics
Tech Domains Python, SQL, AI/ML, Cloud platforms
Staff Data Engineerdata pipelinesAI/MLdata engineeringdata productsAPIsdata governancecloud platformsLLMAI agentsmarketing insightsdata securitydata managementPythonSQLAI/ML solutionsmarketing data

Lack of data engineering experience, No experience with AI/ML solutions, Inability to work remotely, No familiarity with cloud platforms

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