Senior Systems Engineering

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About the role

Job Description Vacancy Status: This posting is for an existing vacancy within the organization and is open to new applications. AI Disclosure: As part of the application process, Artificial Intelligence will be used in the hiring process for this role Work Arrangement : Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Markham or Oshawa office three times per week, at minimum.  The Role The Senior Systems Engineer will join the Systems Engineering team within the Device Data Capture and Data Engineering organization and help define, integrate, and ensure validation coverage of end-to-end vehicle data collection capabilities across embedded systems, cloud services, and data platforms. This role is focused on building strong systems engineering foundations for data engineering and data collection capabilities, including end-to-end systems requirements management, system architecture alignment, verification planning, validation coverage and compliance, integration into vehicle programs, performance monitoring, and operational observability. The role will ensure capabilities are defined with clear requirements, traceability, end to end system architecture, measurable verification strategy, and operational visibility. The successful candidate will serve as a technical systems engineering leader who connects product intent to system behavior, vehicle integration, verification evidence, and operational outcomes. They will collaborate closely with system and software architects, operations, testing, product and program managers, and senior data engineering leadership to ensure capabilities are scalable, observable, compliant, and ready for deployment across vehicle programs.   What You'll Do (Responsibilities) • Lead end-to-end systems requirements management for vehicle data collection and data engineering capabilities, translating product and program needs into clear, testable, and traceable system requirements across vehicle, edge, and cloud components. • Drive systems architecture alignment for DDC capabilities, ensuring requirements, interfaces, operational flows, and deployment models are consistent across embedded agents, gateways, cloud ingestion pipelines, and downstream data platforms. • Own verification planning for new and existing capabilities, including definition of verification strategies, test scopes, entry and exit criteria, coverage expectations, and compliance evidence needed for release readiness and vehicle program integration. • Define and mature systems-level observability requirements so teams can monitor feature performance, fault behavior, service health, configuration uptake, population status, and end-to-end data transport across development, validation, exposure, and production environments. • Establish performance monitoring and capability observability frameworks that make it possible to assess whether features are functioning as expected, whether data sources are producing expected outputs, and whether uploaded data is reaching the intended storage and analytics destinations. • Partner with software, systems, and operations teams to define verification and validation coverage across the DDC capability domains, including logs, metrics, traces, binary files, functional signals, configuration distribution, and vehicle/data lifecycle behaviors. • Ensure robust traceability between capability requirements, architecture decisions, configuration states, deployed campaigns, captured data, and verification evidence so engineering teams can understand what was deployed, where it ran, and under what conditions data was collected. • Support integration of DDC capabilities into vehicle programs by identifying system dependencies, defining readiness cri

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