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General Motors

Builds cars, trucks and SUVs for drivers

Lead System Integration Engineer - Enterprise Transformation

Backend EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 7 years of hands-on experience in integration engineering, software engineering, platform architecture, or enterprise application integration within complex enterprise environments.
  • Proven ability to map dependencies across applications, data layers, identity services, and business processes.
  • A bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.
  • Production-level proficiency in Python and core scripting or automation frameworks.
  • Extensive experience building and supporting enterprise-grade integrations using REST APIs, webhooks, middleware solutions, and ETL or data transformation logic.
  • Strong understanding of cloud-based integration patterns, modern application architecture, Git-based version control, and debugging integration issues across multi-system environments.
  • Experience designing secure, supportable integrations across SaaS platforms and internal enterprise systems.
  • Foundational knowledge of enterprise authentication, authorization, identity integration, and access-control frameworks.
  • Experience working with product managers, engineering teams, technical program managers, security leads, and business stakeholders.
  • Strong written and verbal communication skills, including explaining technical tradeoffs, architecture risks, and engineering decisions to non-technical partners.

Responsibilities

  • Build reusable services, accelerators, and reference integration templates to address recurring connectivity needs consistently.
  • Align integration designs with enterprise data standards, identity guidelines, and security policies.
  • Partner with Security, Privacy, Identity, Information Lifecycle Management, and Retention teams to support workflows processing sensitive or regulated data.
  • Evaluate incoming integration requests and recommend an appropriate technical path using approved platform capabilities, configuration options, or custom engineering.
  • Design, build, and maintain robust, resilient, and observable integrations using APIs, webhooks, scripts, connectors, and middleware services.
  • Define source-to-destination data mappings, transformation logic, exception-handling patterns, and monitoring approaches for reliable operations.
  • Modernize Microsoft-dependent workflows, legacy interfaces, and older automations into scalable, Google-aligned integration patterns.
  • Connect Google Workspace with core GM platforms, including identity services, reporting environments, asset repositories, and approved AI platforms.
  • Support end-to-end workflows that move data and trigger actions across enterprise systems.
  • Design and support coexistence models that enable Microsoft, Google, and internal platforms to interoperate during phased migration waves.
  • Preserve workflow continuity when historical data, inactive-user content, or core systems must remain on legacy platforms during transition.
  • Support cutover sequencing, permissions validation, metadata mapping, and post-deployment stabilization to reduce operational disruption.
  • Partner with transformation Product Leads and Technical Program Managers in business units to integrate Google capabilities into operational processes.
  • Provide technical leadership through design reviews, implementation guidance, and engineering best practices across the program.
  • Author technical designs, dependency maps, operational runbooks, and handover materials to support long-term solution sustainment.
  • Support validation, troubleshooting, and hypercare during rollout and early adoption.

Desired Qualifications

  • Direct experience supporting large-scale Microsoft 365 to Google Workspace migration or coexistence programs.
  • Familiarity with Google Workspace administration, Google Workspace APIs, Google Apps Script, and AppSheet.
  • Experience connecting enterprise workflows to modern data and AI ecosystems such as Gemini Enterprise, Glean, AskGM, and Databricks.
  • Familiarity with corporate data retention, Information Lifecycle Management, privacy frameworks, and regulated data controls in large-scale enterprise environments.
  • Experience supporting automated testing, cutover planning, data validation, hypercare support, and long-term sustainment models.

About the Company

General Motors

Builds cars, trucks and SUVs for drivers

General Motors designs, builds and sells cars, trucks and SUVs for individual drivers and commercial fleets, with gasoline and electric models across mainstream and luxury markets. Its Chevrolet and GMC brands cover pickups and utility vehicles, while Cadillac focuses on luxury and Buick sells passenger vehicles. The group sells vehicles and replacement parts mainly through independent dealers, which handle customer sales, maintenance and repairs. Its captive finance subsidiary, GM Financial, earns revenue from vehicle loans and leases and also finances dealer inventories. General Motors traces its roots to 1908 and is headquartered in Detroit, Michigan.

Company size
10,001+
Company stage
IPO
Headquarters
Detroit, MI
Founded
1908

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