Lead Engineer / Sr. Lead Engineer - System Intelligence

1️. Key Tasks and Deliverables:

• Analyze complex real-time vehicle data from telematics, ECU signals, EOL tests, and dealer management systems within UAT and GPH1 data streams to identify patterns, anomalies, and trends.
• Interpret and validate advanced analytics outputs in the context of vehicle operations to ensure accuracy and relevance for decision-making.
• Develop and maintain interactive dashboards and reports using Power BI and AWS/Databricks to visualize KPIs, system performance, and anomaly alerts for stakeholders.
• Lead field failure and anomaly analytics to detect early issues and provide diagnostic guidance for proactive problem resolution.
• Conduct root cause analysis by investigating correlated vehicle signals and logs; collaborate with engineering teams to recommend corrective actions.
• Deliver tailored intelligence outputs including comprehensive reports, technical briefs, and executive summaries aligned with strategic business objectives.
• Ensure data governance and quality assurance by maintaining high standards of data accuracy, security, and compliance for VES analytics.

2️. Critical Must-Have Deliverables:

• Accurate validation and sign-off of final vehicle intelligence insights before dissemination to Product Development, Customer Care, Service, Quality, and other business units.
• Real-time monitoring dashboards that provide actionable visibility into vehicle performance and failure trends.
• Root cause analysis reports with clear troubleshooting recommendations and collaboration outcomes with engineering teams.
• Compliance with data governance policies ensuring integrity and security of all analytics outputs.

3️. Good-to-Have Deliverables:

• Proactive identification of emerging vehicle performance issues through advanced anomaly detection techniques.
• Continuous improvement suggestions for data visualization and reporting tools to enhance stakeholder engagement.
• Contribution to cross-functional workshops or training sessions to elevate data literacy and analytics adoption within the organization.

4️. Critical Experience Required:

• Minimum of 7 years of experience in vehicle data analytics, telematics, or automotive systems intelligence with demonstrated expertise in real-time data interpretation and root cause analysis.

1. Preferred Industry:

• Automotive, Vehicle Telematics, Connected Vehicles, or related Transportation Technology sectors.

1. Qualifications Required:

• Bachelor’s or master’s degree in engineering (Automotive, Mechanical, Electrical, or Computer Science) or equivalent technical discipline.
• Proven proficiency in data analytics tools such as Power BI, AWS, Databricks, and experience with vehicle diagnostic data.

1. Competencies and Skills: Functional Competencies:

• Expertise in vehicle telematics, ECU signal analysis, and diagnostics data interpretation.
• Strong root cause analysis and problem-solving skills within automotive systems.
• Ability to translate complex analytics into actionable business intelligence.

Tools and Techniques Used:

• Advanced proficiency in Power BI, AWS cloud services, Databricks, and data visualization methodologies.
• Familiarity with CAN/Ethernet data protocols, telematics platforms, and diagnostic trouble code analysis.

Behavioral Competencies:

• Detail-oriented with a strong commitment to data accuracy and quality assurance.
• Effective communicator capable of tailoring technical insights for diverse stakeholder groups.
• Collaborative mindset with the ability to work cross-functionally and influence decision-making.