Position Summary
The Quality Data Analyst is responsible for analyzing Electrical & Electronic Hardware Engineering warranty performance, warranty spending, field quality trends, and product quality indicators to support proactive quality improvement and cost reduction initiatives. The role combines data analytics, quality engineering knowledge, AI adoption, KPI management, process automation, design assessment support, and business intelligence to drive actionable insights across product development, validation, manufacturing, and in-field quality.
The candidate will work closely with Global EHE Quality Engineering teams to monitor warranty performance, identify systemic issues, support root-cause investigations, optimize quality processes, monitor design robustness, and leverage approved Stellantis data analytics and AI platforms to improve engineering decision-making.
Key Responsibilities
Warranty & Quality Analytics
- Analyze global warranty claims, warranty spending, repair cost trends, and field quality performance for Electrical & Electronic Hardware systems.
- Monitor warranty and quality KPIs such as warranty kPPM, warranty spending, incident rates, CPV, repeat failures, service campaign impact, and corrective action effectiveness.
- Use warranty analytics platforms, Power BI reporting, Excel analytics, and data visualization to generate actionable insights for engineering and quality leadership.
- Identify emerging warranty risks, systemic trends, high-cost issues, and recurring failure patterns to support timely decision-making.
KPI Management & Process Automation
- Lead process automation for quality, warranty, and engineering KPI management using approved digital, analytics, and AI-enabled tools.
- Design, develop, and maintain automated dashboards and periodic reports for warranty spending, incidents, kPPM, CPV, quality cost, issue management, design assessment status, lessons learned, and corrective action tracking.
- Integrate data from warranty, issue management, engineering, quality, and SharePoint/Power BI-based sources to improve reporting efficiency, consistency, and data reliability.
- Develop automated alerts, early-warning indicators, and KPI exception reporting for emerging warranty, design, and field quality risks.
- Reduce manual reporting effort by standardizing data flows, automating repetitive KPI reports, and improving reporting cycle time.
Design Assessment & Design Integrity Responsibilities
- Support and coordinate Design Assessment / Design Integrity evaluations for Electrical & Electronic Hardware systems.
- Analyze design assessment outcomes to identify gaps in design robustness, target achievement, validation readiness, risk closure, and lessons learned implementation.
- Develop dashboards and automated trackers for design assessment completion, robustness metrics, open issue status, target achievement status, technical risk indicators, and closure effectiveness.
- Correlate development-phase design assessment findings with warranty issues, plant concerns, validation findings, and field quality performance.
- Collaborate with hardware engineering teams to monitor closure of design gaps and support data-driven improvements to design assessment methodologies.
Data Analytics & AI Adoption
- Actively learn, adopt, and apply Stellantis-approved AI, analytics, and automation solutions relevant to Quality Engineering.
- Apply AI-assisted analytics for trend identification, anomaly detection, early-warning identification, warranty cost forecasting, read-across, and issue prioritization.
- Support predictive quality analytics initiatives and contribute to scalable data-centric quality engineering practices.
- Translate business and engineering problems into analytical use cases, dashboards, reports, and automation opportunities.
Issue Management & Problem Solving
- Support issue management activities including identification of critical warranty issues, investigation prioritization, corrective action tracking, and effectiveness monitoring.
- Conduct statistical analysis and data mining to support root-cause analysis, problem solving, and corrective/preventive action validation.
- Collaborate with engineering, manufacturing, supplier quality, service, and program teams to validate issue status and monitor quality risk reduction.
Process Optimization & Continuous Improvement
- Apply Lean, Six Sigma, quality tools, and structured problem-solving methods to improve reporting efficiency, process maturity, and data quality.
- Identify opportunities to reduce warranty cost through proactive quality actions, digitalization, and process simplification.
- Standardize quality metrics, data definitions, and reporting methods across regions and functions wherever applicable.
- Support continuous improvement initiatives that improve visibility, decision quality, and accountability in the EHE quality process.
Budget, Warranty Cost & Financial Tracking
- Monitor warranty spending, warranty cost drivers, and other quality-related financial indicators linked to Electrical & Electronic Hardware systems.
- Support forecasting and budget management activities related to warranty cost performance, quality cost reduction, and improvement initiatives.
- Provide management visibility on financial impact, cost avoidance opportunities, and high-priority quality cost reduction actions.
Stakeholder Engagement & Reporting
- Work cross-functionally with Electrical Hardware Engineering, Quality Engineering, Program Teams, Manufacturing Quality, Supplier Quality, Service/Warranty organizations, and regional stakeholders.
- Prepare concise leadership-ready summaries, dashboards, and management reports that convert data into clear business and engineering decisions.
- Communicate analytical findings, risks, recommendations, and action plans to technical and non-technical stakeholders.
Required Qualifications
Education
Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline.
Experience
5–10 years of professional experience; experience should not exceed 10 years.
Automotive Background
Prior work experience in Electrical & Electronics area of automotive engineering, hardware development, validation, quality, warranty, or field performance analysis.
Analytics Capability
Strong experience in data analysis, data visualization, dashboarding, KPI reporting, and data storytelling.
Quality Exposure
Exposure to quality tools, issue management, root-cause analysis, corrective action management, and process optimization.
Technical Skills
- Power BI, advanced Excel analytics, data visualization, and dashboard development.
- SQL, Python, Databricks, Power Automate, or equivalent analytics/process automation platforms preferred.
- Experience with warranty data analytics, cost trend analysis, KPI automation, and multi-source data integration.
- Understanding of AI-assisted analytics, predictive quality, anomaly detection, and generative AI use cases in engineering quality.
- Ability to build automated reports, alerts, trackers, and executive dashboards for quality and warranty management.
Quality & Engineering Knowledge
- Warranty management, field quality analysis, issue management, and quality cost monitoring.
- Root Cause Analysis, Corrective Action Management, DFMEA, DRBFM, APQP, statistical tools, and structured problem solving.
- Understanding of automotive Electrical & Electronic Hardware systems, development processes, validation activities, and field performance indicators.
- Exposure to design assessment, design integrity, design robustness, and lessons learned deployment practices.
Preferred Competencies
- Analytical mindset with strong problem-solving and data interpretation skills.
- Passion for learning, adopting, and applying AI and digital analytics solutions.
- Ability to convert complex engineering and warranty data into practical business actions.
- Continuous improvement mindset with ownership of process efficiency and standardization.
- Strong communication, stakeholder management, and leadership-ready presentation skills.
- Customer-focused approach with high accountability for quality and cost improvement outcomes.
Role Success Measures / KPIs
Warranty Cost Impact
Contribution to warranty spending reduction, cost avoidance, and focus on high-impact issues.
KPI Automation
Number and effectiveness of automated KPI dashboards, reports, alerts, and reporting cycle-time reduction.
Data Quality & Timeliness
Accuracy, consistency, and availability of warranty, quality, and design assessment dashboards.
Early Warning & Risk Detection
Identification of emerging warranty trends, anomaly patterns, design risks, and critical quality issues.
Design Assessment Support
Improved visibility of design assessment completion, risk closure, robustness metrics, and lessons learned implementation.
Issue Management Effectiveness
Improved corrective action tracking, closure monitoring, and effectiveness validation.
AI Adoption
Practical use of approved AI and analytics tools to improve speed, insight quality, and decision-making.
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