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# Data Analytics Engineer - Reliability

- **Company:** Brunswick Corporation
- **Location:** Fond du Lac, WI, United States
- **Experience:** Experienced
- **Salary:** $86,500.0 - $139,300.0
- **Contract:** Permanent contract
- **Skills:** Database Queries, Decision Support Systems, Python (Programming Language), Reliability Engineering, Power BI, SQL Databases, Tableau (Software), Powerquery, Data Analytics
- **Published:** July 10, 2026
- **Apply:** https://www.juju.com/job/00000000gfdadi

## About the Role

+ 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

Preferred Qualifications:

 + 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

The hiring range for this position is $86,500 - $139,300 annually. The actual base pay offered will vary based on multiple factors including job-related knowledge/skills, relevant experience, business needs, and geographic location. Compensation decisions are dependent upon the specifics of the candidate's qualifications and the business context.

## Description

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., + 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

Diversity of thought and experiences is fundamental when imagining the unimaginable. Certain skillsets/experiences are necessary; however, others can be developed along the way.


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