Engineering Data Analyst – Reliability and Asset Performance

Glencore Australia; Mount Isa City; On-site; AUD 110,000 - 150,000; Full time

Benefits offered by this job

13% superannuation

Glencore Rewards health discounts

Employee Referral Program

Leadership development programs

Residential role in Mount Isa

Job summary

Glencore Australia’s Mount Isa Mines division seeks an analytical Engineering Data Analyst to support Reliability Engineering and Maintenance through advanced statistical analysis and data quality improvement. You will transform complex maintenance and operational data into meaningful insights to drive asset performance and informed decision-making.

The role emphasizes collaboration with Maintenance, Engineering, Planning and Operations to enhance data capture, standards and compliance,

Qualifications

• Strong background in statistics, mathematics or quantitative analysis.
• Experience with large datasets, statistical modelling and data quality improvement.
• Ability to influence stakeholders to improve data integrity and business outcomes.
• Experience with business intelligence tools is highly regarded.
• Exposure to mining, maintenance, reliability engineering or asset management environments is advantageous.
• SAP experience is desirable.
• Postgraduate qualifications are advantageous but not essential.

Responsibilities

• Apply statistical techniques to maintenance, reliability and operational datasets to identify trends, anomalies and improvement opportunities.
• Analyse equipment performance, downtime, failures and maintenance history to support reliability and asset management decisions.
• Investigate data quality issues, including missing, incomplete or inaccurate work order, failure and downtime information.
• Partner with Maintenance, Engineering, Planning and Operations teams to improve data capture processes, standards and compliance.
• Develop analytical reports, visualisations and insights that translate complex data into practical business recommendations.
• Support continuous improvement initiatives by identifying opportunities to enhance asset reliability, maintenance effectiveness and operational performance.

Skills

Statistical analysis

Data interpretation

Problem solving

Stakeholder engagement

Education

Degree in Statistics, Applied Mathematics, Mathematics, Data Science or related quantitative discipline

Tools

Python

R

JMP

Minitab

SQL

Power BI

Job description

MIM Maintenance Division, Reliability

Mount Isa, Queensland, Australia

Ref. No. 100655

We are seeking an Engineering Data Analyst to support our Reliability Engineering and Maintenance functions through advanced statistical analysis and improvement of engineering data quality. This role will be working a 5/2, 4/3 roster on a 9-hour day.

Mount Isa Mines

Mount Isa Mines is one of the world's largest mining complexes. We operate two mining and processing streams, copper and zinc-lead-silver, to deliver natural resources of enduring value in modern society.

At Mount Isa Mines, we believe in our people. We cultivate an environment of professionalism, ownership, and innovation while prioritizing safety and well-being. Our employee rewards program, market-leading superannuation, and commitment to professional development set us apart.

Learn more about Mount Isa Mines at www.mountisamines.com.au

Your Benefits:

• Competitive remuneration with 13% superannuation (Staff role)
• Access to Glencore Rewards including health insurance discounts, retail offers, and salary sacrifice options
• Employee Referral, Recognition & Reward programs
• Leadership development programs, Ambassador Programs and unrivalled career pathways
• The lifestyle advantage of a residential role in Mount Isa

About The Role

We are seeking an analytical and detail-oriented Engineering Data Analyst to support our Reliability Engineering and Maintenance teams through advanced statistical analysis and data-driven decision making. This role focuses on improving equipment reliability, asset performance and engineering data quality by identifying trends, failure patterns and opportunities for operational improvement.

Working closely with Maintenance, Engineering, Planning and Operations teams, you will transform complex maintenance and operational data into meaningful insights that support asset management strategies and improve business performance. This is an excellent opportunity for a statistically minded professional who enjoys solving real-world operational challenges and influencing positive change through data.

Key responsibilities:

• Apply statistical techniques to maintenance, reliability and operational datasets to identify trends, anomalies and improvement opportunities.
• Analyse equipment performance, downtime, failures and maintenance history to support reliability and asset management decisions.
• Investigate data quality issues, including missing, incomplete or inaccurate work order, failure and downtime information.
• Partner with Maintenance, Engineering, Planning and Operations teams to improve data capture processes, standards and compliance.
• Develop analytical reports, visualisations and insights that translate complex data into practical business recommendations.
• Support continuous improvement initiatives by identifying opportunities to enhance asset reliability, maintenance effectiveness and operational performance.

Required Experience

The ideal candidate will have a strong background in statistics, mathematics or quantitative analysis and the ability to apply analytical thinking to operational and engineering challenges. Experience working with large datasets, statistical modelling, data quality improvement and business intelligence tools is highly regarded. You will possess strong problem-solving skills, a critical mindset and the ability to influence stakeholders to improve data integrity and business outcomes.

You Will Bring:

• Degree in Statistics, Applied Mathematics, Mathematics, Data Science or a related quantitative discipline.
• Strong capability in applied statistical analysis, probability and interpretation of complex datasets.
• Experience using analytical tools such as Python, R, JMP, Minitab or similar.
• Experience with SQL and/or Power BI.
• Demonstrated problem-solving and analytical thinking skills.
• Ability to identify and challenge data quality issues and draw meaningful conclusions from data.
• Strong communication and stakeholder engagement skills.
• Exposure to mining, maintenance, reliability engineering or asset management environments is advantageous.
• SAP experience is desirable.
• Postgraduate qualifications are advantageous but not essential.

At Glencore, our people are the foundation of our success, and we are committed to creating a workplace where our values guide everything we do. Safety is our first priority - we never compromise on it. We act with Integrity, choosing to do what's right even when it's challenging. We take Responsibility for our actions and strive to make a positive impact. Through Openness, we communicate honestly and encourage meaningful dialogue. We embrace Simplicity, focusing on what truly matters and avoiding unnecessary complexity. And with Entrepreneurialism, we welcome new ideas and continuously seek better, safer and more efficient ways of working.

Applications Close: 28 th of September