Data Analytics Engineer – Reliability

As a Data Analytics Engineer – Reliability, you will support data-driven decision making by transforming PD&E test & validation data, warranty, customer usage and reliability data into clear, actionable insights. This role focuses on strong analytical reasoning and statistical rigor to support engineering, quality, and leadership teams.

Responsibilities

Analyze test & validation data, field performance, and customer usage data to identify trends and emerging reliability risks; Apply statistical and analytical methods to understand variation, uncertainty, and key drivers; Develop and maintain Power BI and/or Tableau dashboards and standardized reporting; Build and validate SQL-based data sources and support data modeling efforts; Use Python for deeper analysis, automation, or advanced exploration as needed; Partner with IT and cross-functional teams to ensure data quality, consistency, and governance; Communicate insights clearly to technical and non-technical stakeholders

Requirements

Bachelor’s degree in a quantitative field (Data Analytics, Statistics, Engineering, or similar); 3–6 years of experience in data analytics, BI, reliability, or quality analytics; Strong analytical, statistical, and problem-solving skills; Strong SQL skills; experience with Power BI and/or Tableau; Working knowledge of Python; High attention to data accuracy and analytical rigor

Nice to have

Experience with warranty, reliability, durability, or customer usage data; Familiarity with Power BI data modeling, DAX, or Power Query; Exposure to Six Sigma, reliability engineering, or quality systems; Experience working in cross-functional engineering or operations environments

Benefits

Annual discretionary bonus; medical; dental; vision; paid vacation; 401k (up to 4% match); Health Savings Account (with company contribution); well-being program; product purchase discounts; relocation