Quality Analytics Engineer III

Generac Power Systems•Waukesha, WI

About The Position

The Analytics Engineer III leads complex analytical initiatives, from defining data strategy to deploying predictive and analytical solutions that improve product quality, operational performance, and customer experience. The role partners with quality, engineering, operations, and executive leadership to influence strategic decisions, guide analytical investigations, and scale self-service analytics. It combines deep technical skills with business acumen and mentorship. The position architects reporting frameworks and data models across quality, warranty, manufacturing, and operational analytics; develops advanced models and studies; partners with data engineering on ETL processes and scalable infrastructure; and leads process automation, KPI standardization, and data governance efforts. The role also mentors junior team members and enables business users to apply analytics in decision-making.

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Analytics, Engineering, Industrial Engineering, or a related field.
At least 5 years of experience in analytics, including significant experience in data strategy, business intelligence, and advanced analytics.
Demonstrated experience supporting quality, warranty, manufacturing, reliability, operational performance, or continuous improvement initiatives through data-driven insights.
Expert-level SQL and Python or R.
Deep experience with data modeling, cloud platforms such as Databricks, and large-scale data systems.
Advanced proficiency in BI tools and statistical modeling packages.
Experience developing dashboards, scorecards, and analytical solutions for quality and operational decision-making.
Experience with power generation development and technology.
Strong stakeholder management skills, including influencing without authority.
Proven ability to translate analytics into business strategy and executive narratives.
Ability to communicate complex analytical findings to technical and non-technical stakeholders and drive action through data-driven recommendations.

Nice To Haves

Master's degree in a quantitative field.
Experience with trend analysis, root cause analysis, KPI development, statistical analysis, and process improvement methodologies.

Responsibilities

Identify opportunities for analytics to improve product quality, reliability, operational effectiveness, and customer satisfaction.
Lead requirements gathering for complex, cross-functional initiatives.
Architect scalable reporting frameworks and advanced data models across quality, warranty, manufacturing, and operational analytics.
Oversee delivery of high-impact dashboards and insights for executive-level reporting.
Develop analytical and predictive models to identify quality trends, warranty drivers, failure patterns, process variation, and emerging product risks.
Design and validate analytical studies evaluating corrective actions, process improvements, quality initiatives, and operational performance outcomes.
Apply statistical techniques to identify trends, anomalies, and opportunities for continuous improvement.
Partner with data engineering to design robust ETL processes and scalable infrastructure.
Drive improvements in data architecture for quality, warranty, manufacturing, supplier, and operational analytics, including real-time data integrations.
Lead initiatives to automate data processes and improve operational efficiency.
Standardize quality and operational KPIs and promote data governance best practices.
Drive adoption of consistent metrics, reporting methodologies, and data standards for quality performance management.
Mentor junior team members.
Develop training and tools for business users to champion self-service analytics.
Support quality and operational teams in using analytics for data-informed decisions.