Job Description:
About the Role
Nextpower is seeking a Staff Reliability Engineer to build the quantitative foundation for reliability decisions across the product lifecycle. The role will focus on the early and late stages of new product development: translating operating missions and product architecture into reliability models and targets, then connecting test, manufacturing, warranty, and field evidence to a clear view of fleet performance and cost.
In this role, you will work with Systems, Electrical, Mechanical, Power Electronics, Validation, Quality, Service, Product Management, Finance, and Data teams. Your analyses will help teams make design and launch decisions, understand uncertainty, identify emerging field risks, and feed operational learning back into future product requirements and architectures.
Key Responsibilities
Reliability Analytics and Modeling
•Translate customer use conditions, service-life expectations, availability needs, and business objectives into measurable reliability requirements, metrics, assumptions, and evidence plans.
•Develop and maintain product mission profiles that describe geography, ambient and internal conditions, operating states, duty cycles, load levels, and exposure over time; document data sources and uncertainty.
•Build and maintain system and subsystem reliability models, including Reliability Block Diagrams and fault trees, to evaluate architecture, redundancy, dominant contributors, reliability allocations, and sensitivity to assumptions.
•Develop component and system reliability predictions using applicable parts-count, parts-stress, supplier, test, and field evidence. Select methods appropriate to the available data and product maturity, and clearly state limitations.
•Apply reliability statistics to life and event data, including Weibull and other life distributions, censored data, confidence bounds, accelerated-life relationships, reliability growth, and Bayesian updating where appropriate.
•Integrate analytical outputs with DFMEA, architecture reviews, design trade studies, and development gates so that quantified risk informs design priorities and readiness decisions.
Warranty and Field Reliability Analytics
•Develop and maintain a field reliability data model that connects product configuration and serial or cohort information with exposure, telemetry, service events, returns, failure analysis, and warranty claims.
•Define consistent metric definitions and denominators for field performance, including failure rate, cumulative failures, availability or downtime measures where applicable, and warranty incidence and cost.
•Analyze warranty, service, return, and field data to identify trends, shifts, recurring failure modes, affected populations, and emerging risks; quantify uncertainty and distinguish confirmed findings from hypothesis.
•Develop warranty life and cost analyses that estimate claim frequency and cost over time, assess sensitivity to assumptions, and support product, finance and business planning.
•Build and maintain dashboards and recurring reports that present reliability performance by product, configuration, region, age, exposure, and failure mode, with clear definitions and decision-focused interpretation.
•Track early-launch performance and reliability growth using pilot and field evidence; update predictions as exposure accumulates and communicate material changes to forecasts and risk outlooks.
•Feed field findings into future mission profiles, reliability requirements, model assumptions, design priorities, supplier actions, and validation evidence plans.
Data, Tools and Cross-Functional Partnership
•Partner with Data Engineering and business system owners to improve data availability, traceability, quality, and repeatability across engineering, manufacturing, service and warranty sources.
•Use statistical and analytical tools such as Python, JMP or R and visualization platforms such as Power BI or Tableau to develop reproducible analyses and practical reporting workflows.
•Present results to technical and business audiences, explaining methods, assumptions, confidence, data gaps and recommended actions in clear written reports and product reviews.
•Coach engineering and business partners in the interpretation of reliability metrics and statistical evidence, including the implications of exposure, sample size, censoring and model uncertainty.
Qualifications Required
•Bachelor’s degree in Engineering, Reliability Engineering, Applied Statistics, Data Science or a related quantitative field; equivalent experience may be considered.
•Typically 10 years of experience in reliability engineering, reliability analytics, product quality analytics, or a related quantitative engineering role.
•Demonstrated experience with reliability modeling and statistics, including mission profiles, reliability block diagrams, MTBF or failure-rate analysis, life-data analytics, and confidence intervals.
•Strong proficiency with statistical and modeling packages like JMP, Minitab, Reliasoft Weibull , BlockSIM plus experience creating dashboards with Python or R and SQL and recurring analytical reports using business intelligence tools.
•Experience analyzing product, test, manufacturing, warranty, service, or field data and translating results into engineering or business decisions.
•Strong written and verbal communication skills, with the ability to explain technical results, assumptions, and uncertainty to cross-functional stakeholders.
Preferred
•Experience with utility-scale power conversion, inverters, renewable energy systems, industrial electronics, or other complex products deployed in large fleets.
•Experience developing warranty cost or life projections, early-launch forecasts, reliability growth models, or field performance dashboards.
•Familiarity with Bayesian methods, accelerated life modeling, reliability allocation, availability modeling, and product genealogy or configuration data.
•Experience with ReliabSoft, JMP, Minitab, PowerBI, Tableau, or comparable tools; Certified Reliability Engineer (CRE) or equivalent certification.
At Nextpower, we are driving the global energy transition with an integrated clean energy technology platform that combines intelligent structural, electrical, and digital solutions for utility-scale power plants. Our comprehensive portfolio enables faster project delivery, higher performance, and greater reliability, helping our customers capture the full value of solar power. Our talented worldwide teams are redefining how solar power plants are designed, built, and operated every day with smart technology, data-driven insights, and advanced automation. Together, we’re building the foundation for the world’s next generation of clean energy infrastructure.
We are Nextpower