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Equipment Maintenance Data Analyst

Bloom Energy -
Fremont, CA

Apply Now

Job Details

Full-time
$72,100 - $103,900 a year
7 days ago

Qualifications

Data visualization software proficiency
SQL
Business intelligence tools
Data analysis software
Database software proficiency

Full Job Description

Our team at Bloom Energy embraces the unprecedented opportunity to change the way companies utilize energy. Our technology empowers businesses and communities to responsibly take charge of their energy. Our energy platform has three key value propositions: resiliency, sustainability, and predictability. We provide infrastructure that is flexible for the evolving net zero ecosystem. We have deployed more than 30,000 fuel cell modules since our first commercial shipments in 2009, sending energy platforms to data centers, hospitals, manufacturing facilities, biotechnology facilities, major retail stores, financial institutions, telecom facilities, utilities, and other critical infrastructure customers around the world.

Our mission is to make clean, reliable energy affordable globally. We never stop striving to improve our technology, to expand and improve our company performance, and to develop and support the many talented employees that serve our mission!

We are seeking a detail-oriented and analytical Equipment Maintenance Data Analyst to collect, process, and perform statistical analyses on manufacturing datasets. The ideal candidate will translate data into actionable insights that support the Maintenance Management team in strategic decision-making, improve business performance, and drive operational efficiency. This role will report to the Director, Maintenance Manufacturing and will be based in Fremont, CA . This is a fully on-site, in office role five days a week.

Key Responsibilities

Collect, clean, and validate data from multiple sources to ensure accuracy and reliability
Analyze large datasets to identify trends, patterns, and insights and give graphical representation of results.
Develop and maintain dashboards, reports, and data visualizations using tools such as Power BI, Tableau, or Excel
Partner with cross-functional teams to understand business requirements and provide data-driven recommendations
Interpret data and communicate findings to stakeholders in a clear, concise manner
Perform ad hoc analysis to support business initiatives and decision-making
Monitor data quality and troubleshoot data-related issues
Document methodologies, processes, and data definitions

Required Qualifications

Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Economics, or a related field preferred
Understanding of Maintenance practices, MTTR, MTBF, OEE are preferred
2–5+ years of experience in data analysis or a similar role
Strong proficiency in SQL and experience working with relational databases
Advanced skills in Excel (e.g., pivot tables, formulas)
Experience with data visualization tools (e.g., Power BI, Tableau)
Knowledge of statistical analysis techniques and tools (e.g., Python, R)
Strong analytical thinking and problem-solving skills

Bloom Energy is an equal opportunity employer and makes employment decisions on the basis of merit. We are committed to compliance with all applicable laws providing equal employment opportunities. All qualified applicants, will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status, or on the basis of disability. Bloom Energy makes reasonable accommodations, consistent with applicable laws, for the known physical or mental limitations of an otherwise qualified applicant or employee with a disability, who can perform the essential job functions, unless undue hardship would result.

Bloom Energy is committed to fair and equitable compensation practices. The total compensation for this position includes standard company benefits and is based on various factors including, but not limited to, relevant skills and experience.

#BEI2024

#LI-JG1

Salary Ranges:

$72,100.00 - $103,900.00

Apply Now

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