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Job Description:

The ADAS (Advanced Driver Assistance Systems) Data Anlaytics team is seeking a motivated, tech-savvy Associate Engineer to join our team. This is a unique, "hybrid" technical role designed for someone who wants to bridge the gap between the physical world of automotive testing and the digital world of big data. In this role, you won't just sit behind a screen. You will be a key part of the feedback loop that makes ADAS features (like BlueCruise) exciting experiences for our customers. You will spend time in development vehicles in Dearborn validating data collection processes and then use cloud-based tools to analyze that data. We are looking for a problem-solver who is excited to learn the "nuts and bolts" of vehicle technology while mastering modern data engineering stacks.

Skills Required:

+ Analytical skills, Troubleshooting (Problem Solving)

+ Analytical skills – Proficiency in end-to-end data analysis, including data ingestion, trend identification, and performance tracking. An ideal example would be a candidate who has designed a suite of tests, visualized the results through automated plotting, and synthesized complex data points into actionable conclusions or technical recommendations.

+ Troubleshooting (Problem Solving) - Demonstrated ability to methodically diagnose technical failures, particularly within vehicle-based systems. For instance, if a feature fails to activate during a test drive, the candidate should be able to walk through their logical process: from checking logs and hardware connections to identifying software bugs. This also includes resolving environment-specific issues, such as troubleshooting failed software deployments or configuration errors on test devices.

Skills Preferred:

+ SQL – Ability to write complex SQL queries to extract, transform, and clean raw data from relational databases. The candidate should be comfortable using joins, aggregations, and subqueries to turn "noisy" data into structured datasets ready for metric generation.

+ Big Query – Hands-on experience navigating the Google Cloud Platform (GCP) environment, specifically using BigQuery to query massive datasets. This includes an understanding of cost-efficient querying practices and the ability to manage data partitioned across different tables.

+ Data Analysis – Beyond just viewing charts, this involves "storytelling with data." We are looking for the ability to look at disparate data sources, identify anomalies or correlations, and translate those findings into a clear narrative that explains system behavior.

+ Data Governance – Experience implementing or adhering to frameworks that ensure data integrity, security, and privacy. This includes understanding PII (Personally Identifiable Information) handling, managing user access permissions, and ensuring data usage complies with organizational or regulatory standards.

+ Data/Analytics dashboards – Experience building intuitive, interactive visualizations (using tools like Tableau, Looker, or Power BI). The candidate should be able to design dashboards that allow stakeholders to filter data and drill down into specific trends or timeframes effortlessly.

+ Testing – Experience executing structured in-vehicle test plans. This includes validating that specific features (e.g., ADAS, Infotainment, or Connectivity) meet functional requirements under various real-world scenarios and documenting "edge case" failures that occur outside of standard operating conditions.

+ Business Intelligence - The ability to bridge the gap between technical data and business strategy. An ideal candidate uses BI tools to monitor Key Performance Indicators (KPIs) and provides insights that directly influence product roadmaps or operational decisions.

Experience Required:

+ At least 1 year of experience in data analysis, analytics, or systems level vehicle testing

Education Required:

+ Bachelor's Degree

Key Responsibilities:

+ Hands-On Vehicle Testing: Participate in in-vehicle test drives to validate that data collection functions and triggers are working correctly.

+ Data Analysis & Support: Assist in performing deep-dive analytics on collected datasets to ensure the quality and accuracy of the information being sent to our cloud.

+ Data Modeling: Learn to write and maintain data models using SQL and Dataform within the Google BigQuery environment.

+ Dashboarding: Build and update automated dashboards to help the team track the progress of data collection and system health.

+ Troubleshooting: Work with senior engineers to identify why data might be missing or corrupted, helping to "debug" the pipeline from the vehicle sensor to the cloud.

+ Collaboration: Work across teams in Dearborn to coordinate vehicle availability and test schedules.

#LI-SK11 #LI-Hybrid

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