Quality Data Analytics - Senior Engineer

Quality Data Analytics - Senior Engineer

 

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• Develop and maintain analytical solutions for customer-quality data, including Warranty, NPS, J.D. Power IQS/VDS/APEAL, and related quality metrics.
• Integrate, cleanse, validate, and transform data from multiple sources to create reliable, analysis-ready datasets. Apply data-quality checks and document assumptions, definitions, and limitations.
• Use statistical analysis, trend analysis, segmentation, and other appropriate analytical methods to identify emerging issues, customer pain points, drivers of performance, and opportunities for corrective action.
• Build and maintain recurring reports, dashboards, and visualizations using tools such as SQL, Excel/VBA, Power BI, and Power Apps, as appropriate to the solution.
• Automate repeatable data-preparation, analysis, and reporting tasks to improve efficiency, consistency, and timeliness while maintaining appropriate validation and controls.
• Translate analytical findings into clear, evidence-based recommendations. Present results, risks, and proposed actions to technical and non-technical stakeholders in review meetings.
• Serve as a technical point of contact for stakeholder questions about data definitions, analytical methods, report results, and interpretation of quality metrics.
• Gather and document stakeholder requirements; incorporate feedback into reporting and analytical solutions while maintaining traceability of changes.
• Perform quality checks on analytical code, datasets, calculations, dashboards, and reports before release; investigate discrepancies and resolve data or logic issues.
• Identify process and technology improvements across Warranty, NPS, and J.D. Power analysis workflows. Develop project proposals that define the problem, scope, approach, expected benefits, and measures of success.
• Coordinate cross-functional contributors, dependencies, and actions to support delivery of analytics and automation projects.
• Coach team members on data preparation, analytical methods, reporting tools, and quality-control practices.
• Maintain current knowledge of relevant analytical methods, reporting technologies, and industry practices.

 

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• Monthly reports and dashboards showing Warranty, NPS, and J.D. Power IQS/VDS/APEAL performance, trends, key drivers, and customer pain points.
• Documented data definitions, validation checks, analytical assumptions, and reporting logic for recurring outputs.
• Meeting materials summarizing findings, recommendations, decisions, action owners, and due dates.
• Process pain-point assessments identifying opportunities for analytics, automation, and workflow improvement.
• Project proposals specifying objectives, scope, solution approach, stakeholders, expected outcomes, and success measures.
• Automated or standardized reporting solutions with appropriate documentation and validation procedures.

 

Education and Experience

• Bachelor’s degree in Engineering, Data Analytics, Statistics, Computer Science, Information Systems, or a related discipline.
• Five or more years of relevant experience in data analytics, business intelligence, quality analytics, or reporting automation.
• Experience working with large or multi-source datasets and delivering recurring analytics or reporting solutions is preferred.

 

Technical Skills & Knowledge:

• Proficiency in SQL for querying, joining, aggregating, and validating data.
• Hands-on experience with one or more business-intelligence or analytics platforms, such as Power BI, including data modeling, dashboard development, and report publishing.
• Advanced Excel skills, including complex formulas, PivotTables, data modeling, and VBA or equivalent automation techniques.
• Experience developing or supporting workflow and reporting automation using Power Apps or comparable tools.
• Working knowledge of statistical methods and their application to quality and customer-experience problems, such as descriptive analysis, trend analysis, segmentation, correlation, and root-cause investigation.
• Ability to assess data completeness, accuracy, consistency, and validity; investigate anomalies; and communicate data limitations.
• Understanding of customer-quality measures, including NPS, Warranty, and J.D. Power metrics such as IQS, VDS, and APEAL, or the ability to learn and apply them.
• Strong analytical problem-solving skills, with the ability to convert business questions into measurable analyses and actionable recommendations.
• Effective written and verbal communication skills, including the ability to present technical results to stakeholders with varying levels of analytical expertise.
• Proficiency in Microsoft Office applications, particularly PowerPoint, Word, Excel, and Outlook.

Experience Level

Senior Level