Aptiv Hiring: Data Analytics Engineer 2026:-
The role focuses on vehicle data mining, ADAS (Advanced Driver Assistance Systems) validation, AI/ML support, embedded-level debugging, vehicle signal analysis, and data-driven problem-solving.
Complete job details are given below.
| Company : | Aptiv |
| Job Role : | Data Analytics Engineer |
| Job Type : | Full-Time |
| Experience : | 2+ Years |
| Salary : | As per Company Standards |
| Last Date to Apply : | ASAP |
Role Overview:-
As a Data Analytics Engineer at Aptiv, you will work on vehicle data mining, exploratory data analysis, signal analysis, and AI/ML validation activities related to automotive systems and ADAS features.
You will use Python and data science tools to analyze vehicle logs, identify anomalies, support issue triage, and assist engineering teams with root-cause analysis.
The role also involves understanding vehicle communication protocols such as CAN and Ethernet, analyzing Electronic Control Unit (ECU) logs, supporting vehicle testing, and validating data collected from sensors and embedded systems.
You will collaborate with algorithm development teams, systems engineers, validation engineers, and project managers to improve data quality, support system debugging, and strengthen the reliability of automotive technologies.
Experience requirement: The supplied job description specifies 2+ years of experience, making this an experienced-candidate role rather than a general fresher internship.
Educational Requirements:-
Candidates should have a Bachelor’s or Master’s degree in a relevant technical discipline.
Relevant educational qualifications include:
- B.E. / B.Tech in Computer Engineering
- B.E. / B.Tech in Electrical and Electronics Engineering
- B.E. / B.Tech in Electronics and Communication Engineering
- B.E. / B.Tech in Computer Science Engineering
- B.E. / B.Tech in Embedded Systems Engineering
- B.E. / B.Tech in Automotive Engineering
- B.E. / B.Tech in Systems Engineering
- B.Sc. / M.Sc. in Data Science or a related technical discipline
- M.E. / M.Tech in relevant engineering or data science fields
Mandatory Qualification: A Bachelor’s or Master’s degree in a relevant field, as specified in the job description.
Key Skills:-
Technical Skills
- Python programming
- Vehicle data mining and exploratory data analysis
- Data science and analytics tools
- CAN communication protocol
- Automotive Ethernet
- Vehicle signal and log analysis
- ECU log analysis
- Embedded systems fundamentals
- MATLAB
- SQL / DBQL, as referenced in the supplied listing
- Linux operating system
- Machine learning algorithms
- AI/ML validation workflows
- Data quality assessment
- Feature analysis and labeling support
- Signal-to-algorithm correlation
- Root-cause analysis
- Vehicle instrumentation and data logging
Automotive & Functional Skills
- Advanced Driver Assistance Systems (ADAS)
- Automotive data analytics
- Vehicle communication protocols
- Sensor data analysis
- Embedded-level debugging
- Vehicle testing and validation
- Event extraction and issue triage
- CAN and Ethernet trace interpretation
- Data collection and validation
- Software and system validation
- ADAS system architecture
- Sensor-to-ECU data flow
- Software-in-the-Loop (SIL) testing
- Automotive simulation environments
- Engineering documentation
Preferred Tools & Technologies
- CANalyzer
- CANoe
- MATLAB
- Basic C / C++
- Signal processing
- Linux-based debugging
- Machine learning frameworks and analytical tools
- Agile / Scrum development practices
Soft Skills
- Strong analytical and problem-solving abilities
- Curiosity and willingness to learn
- Structured approach to problem-solving
- Attention to detail
- Collaboration and teamwork
- Clear technical communication
- Ability to work with cross-functional teams
- Adaptability and resilience
- Openness to feedback and mentorship
- Ownership and accountability
- Continuous improvement mindset
Roles & Responsibilities:-
1. Vehicle Data Mining & Analytics
- Perform vehicle data mining and exploratory data analysis using Python and data science tools.
- Analyze large vehicle datasets to identify patterns, trends, and anomalies.
- Support the extraction and analysis of events related to customer-reported and internal engineering issues.
- Analyze vehicle signals and logs, including CAN and Ethernet data.
- Identify abnormal signal behavior and potential vehicle performance concerns.
- Apply structured problem-solving techniques to support engineering investigations.
- Help improve data analysis workflows and tools used by the engineering team.
2. AI & Machine Learning Support
- Support AI/ML validation workflows for Advanced Driver Assistance Systems (ADAS) features.
- Explore datasets and assess data quality for machine learning applications.
- Assist with feature analysis, data labeling, and dataset preparation.
- Review basic machine learning performance metrics.
- Identify data issues that may affect model behavior, including noise, missing signals, and data drift.
- Support investigations into relationships between vehicle data and algorithm performance.
- Develop an understanding of how machine learning models interact with embedded ADAS systems.
3. Embedded-Level Debugging & System Understanding
- Support embedded-level issue triage and technical investigations.
- Analyze ECU logs to identify potential system-level problems.
- Interpret vehicle communication traces and signal behavior.
- Assist in correlating vehicle signals with algorithm outputs.
- Support debugging activities involving sensors, embedded software, and analytics outputs.
- Develop an understanding of ADAS architecture and data flow from sensors to ECUs, analytics, and validation systems.
- Collaborate with senior engineers to investigate system-level issues and potential root causes.
4. Vehicle Testing & Data Collection
- Participate in hands-on vehicle testing and data collection under the guidance of senior engineers.
- Support vehicle instrumentation and data logging setup.
- Assist in validating collected vehicle data before analysis.
- Check data completeness and quality against analysis and validation requirements.
- Support the collection of vehicle signals and logs for engineering investigations.
- Help ensure data collection activities meet project requirements.
- Document testing observations and communicate identified issues to the engineering team.
5. ADAS System Validation
- Support validation activities related to ADAS features and automotive systems.
- Assist in preparing and reviewing datasets used in testing and validation.
- Help identify data inconsistencies that may affect validation results.
- Work with systems and validation engineers to investigate anomalies.
- Contribute to maintaining accurate validation records and technical documentation.
- Follow established development and validation processes, including the ADAS V-cycle.
6. Cross-Functional Collaboration
- Work closely with algorithm development teams.
- Collaborate with systems engineers and validation engineers.
- Coordinate with project and engineering managers on assigned activities.
- Communicate data analysis findings and potential issues clearly.
- Participate in technical discussions and problem-solving sessions.
- Support engineering teams by providing accurate and timely analytical outputs.
7. Process Improvement & Documentation
- Follow established engineering development, validation, and documentation procedures.
- Maintain clear records of data analysis, testing, and issue investigations.
- Contribute to improving data analytics tools and workflows.
- Identify opportunities to improve analysis efficiency and data quality.
- Support consistent and repeatable analytical processes.
- Apply feedback from senior engineers to improve technical performance and work quality.
About Company:-
Aptiv is a global technology company that develops advanced solutions for mobility, automotive safety, vehicle automation, and intelligent systems.
The company works on technologies that support advanced driver assistance systems, autonomous driving, connected vehicles, embedded systems, and software-defined mobility.
Aptiv brings together engineering, software, electronics, and data analytics to help automotive manufacturers develop safer, smarter, and more reliable vehicle technologies.
The company emphasizes innovation, collaboration, continuous learning, inclusion, and professional development, providing opportunities for engineers to contribute to next-generation automotive solutions.
Aptiv Hiring: Data Analytics Engineer 2026 Application Process:-
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
