Test Engineering, Data Engineering - Systems QA

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: this role is categorized as hybrid. This means the successful candidate is expected to report to the office three days per week, ut the team  the data engineering systems qa team verifies the end-to-end data plane and control plane ecosystem connecting millions of intelligent vehicles to cloud platforms.

Our mission is to ensure that vehicle data streaming from embedded controllers reaches cloud data platforms, mobile apps, and operational monitoring services with zero loss, while rigorously testing and monitoring controlled configuration rollouts and campaign operations across the fleet.
The role  we are seeking a candidate in test engineering to strengthen our system verification and quality assurance team. This role is crucial for ensuring the integrity, scalability, and performance of our end-to-end data plane and control plane pipelines, extending from embedded vehicle components to cloud-based analytics platforms. In this role, you will develop automated verification for bench and vehicle levels of connected vehicle features, validating high-throughput telemetry ingestion, and vehicle health monitoring.

The successful candidate will drive testing rigor across both physical test assets and cloud environments, ensuring our systems meet demanding quality, safety, and performance requirements.
What you'll do (responsibilities)   end-to-end test strategy & execution: formulate, automate, and execute comprehensive test plans covering both data plane and control plane interfaces across vehicle edge, cloud infrastructure layers and beyond.
Hardware-in-the-loop (hil) testing: configure, maintain, and execute tests on benches, virtual test environments (sil), and instrumented vehicle setups.
System integration & performance testing: conduct thorough integration, latency and throughput testing across edge and cloud boundaries; identify system bottlenecks and propose optimizations.
Data integrity & pipeline verification: validate data serialization, pipeline throughput, deduplication, and database persistence across ingestion feeds and analytical storage layers.
Observability & defect triage: leverage monitoring dashboards, metrics, and distributed tracing to proactively detect anomalies, perform deep root-cause analysis, and track defect resolution across hardware and software teams.
Collaborative engineering: partner closely with embedded software developers, cloud platform teams, and system architects to facilitate seamless system integration and drive design-for-testability.
Ci/cd & test automation: build and maintain automated regression suites integrated into ci/cd pipelines to enforce quality gates for every software and firmware release.
Documentation & quality standards: maintain rigorous documentation of system test benches, test frameworks, test results, and performance baselines.
Your skills & abilities (required qualifications)   bachelor's degree in computer science, software engineering, electrical engineering, computer engineering, or a related technical discipline.
3+ years of experience in software or systems testing, with exposure to embedded systems, connected devices, or iot ecosystems.
Demonstrated hands-on experience with hardware-in-the-loop (hil) testing, including test setup, wire harness troubleshooting, signal/bus simulation, test execution, and results analysis.
Proficiency in python for automated testing, test harness creation, and data processing.
Practical ability to inspect, read, and debug compiled code written in c/c++, rust, or java.
Working knowledge of sql for querying relational and analytical databases to verify data persistence and message integrity.

Experience with operating systems such as linux, qnx, or android.
Solid understanding of agile methodologies, git version control, and ci/cd automated test integration.
What can give you a competitive edge (preferred qualifications)   experience with software observability, including monitoring, logging, metrics, dashboards, and alerting.
Hands-on experience with observability and monitoring platforms such as datadog, grafana, or open telemetry.

Experience with data and analytics platforms such as databricks, apache spark, or apache kafka.
Familiarity with cloud platforms such as aws or…