Customer Usage Data - Connected Vehicle Engineer Technical Expert at Segula Technologies

Auburn Hills, Michigan, United States -

Full Time

Start Date

Immediate

Expiry Date

08 Jun, 26

Salary

0.0

Posted On

10 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Strategy, Pipeline Development, Big Data, ADAS, Root Cause Analysis, CAN Bus, ETAS INCA, VehicleSpy, SQL, JSON, Databricks, Snowflake, Palantir-Foundry, Power BI, Project Management, Test Engineering

Industry

Engineering Services

Description

Company Description Do you want to shape the world of tomorrow and work on innovative projects? Then you're a good fit for us! We are a global engineering group with 15,000 employees and 140 locations worldwide. With our services, we are driving the topics of energy efficiency, climate protection and decarbonization and developing tech industries into new dimensions. In the United States, the world of SEGULA Technologies Experts revolves around industries such as automotive, energy and life sciences. As an independent player, we support OEMs and suppliers with personal engineering services. Take advantage of new opportunities and take on exciting tasks and attractive positions with direct customer assignment. Job Description We are seeking a highly skilled Connected Vehicle Data Technical Expert to join our Vehicle Development & Validation team. In this critical role, you will define and implement the strategy for collecting, storing, and analyzing large-scale customer usage data from our connected vehicle fleet. Your work will directly influence product development, system engineering, and the resolution of complex warranty and quality issues across our internal combustion, hybrid, and electric vehicle lineups. You will act as the bridge between software-defined vehicle policies and real-world engineering insights, ensuring that our data pipelines are robust, accurate, and actionable. Key Responsibilities Data Strategy & Policy: Develop and institute corporate standard protocols for on-board calculations (synthetic channels, histograms, event counts, and triggered time-series data). Pipeline Development: Lead the validation of over-the-air (OTA) big data, including infrastructure standards, data cleaning/scrubbing, aggregation routines, and the development of advanced dashboards for visualization. Engineering Insights: Utilize large-scale customer usage data to optimize test schedule development and provide actionable insights for ADAS L1/L2 feature refinement. Issue Resolution: Support the root-cause analysis of customer issues for ICE, PHEV, and BEV platforms by validating engine, battery, thermal, and trip telemetry. Cross-Functional Collaboration: Partner with the Connected Vehicle App development team to enhance data collection capabilities, user interfaces, and output standards. Mentorship: Train and guide engineering peers on vehicle policy creation, signal output, and advanced big data query/analysis techniques. Qualifications Education: BSME (Bachelor of Science in Mechanical Engineering). Experience: Proven experience in full vehicle testing, development, and releasing. Technical Proficiency: Deep understanding of Vehicle CAN Bus broadcast and diagnostic signals. Advanced experience with Big Data platforms (e.g., Snowflake, Databricks, Palantir-Foundry, Power BI). Proficiency in data manipulation languages (SQL, JSON). Hands-on experience with industry-standard tools such as ETAS INCA, VehicleSpy, and Aptiv. Skills: Strong project management and test engineering capabilities. Preferred Qualifications Education: MSME (Master of Science in Mechanical Engineering). Certifications: Six Sigma and/or formal Root Cause Analysis certification. Additional Information All your information will be kept confidential according to EEO guidelines. Contract/country: Unlimited Job family: Technical Direction and Expertise

Responsibilities

The role involves defining and implementing the strategy for collecting, storing, and analyzing large-scale customer usage data from connected vehicles to influence product development and resolve quality issues. Key duties include developing data protocols, leading big data pipeline validation, providing engineering insights from usage data, and supporting root-cause analysis across vehicle platforms.