QUALIFICATIONS AND EXPERIENCE

• Engineering or Technical Qualifications – All disciplines considered but need to have minimum 5 years industry and site experience, hands-on field and practical experience coupled with a technical qualification will be highly regarded.
• Root Cause Analysis (Required) — formal training and proven track record in delivering high-quality investigations.
• Data Analysis (Required) — ability to interrogate large datasets to identify performance gaps, trends and improvement opportunities.
• Power BI Development (Required) — capable of building dashboards from scratch and integrating multiple data sources.
• VCAT II – Vibration Analysis (Preferred) — qualification and hands-on experience with interpretation and diagnosis.
• Oil Analysis (Preferred) — solid working knowledge; formal training desirable.
• Improvement Project Delivery (Preferred) — experience in identifying, prioritising, and executing initiatives that deliver measurable results.

ABOUT US

Be part of something big. Fortescue is leading the world with our plan to decarbonise our iron ore operations, projects that harness renewable energy and the development of technology that will change our planet forever.

• Conduct detailed technical analysis of downtime events, work management practices, and operational performance.
• Develop business cases for improvement initiatives and cost-reduction opportunities.
• Create and maintain advanced dashboards and reporting tools in Power BI, integrating data from sources such as Snowflake.
• Act as the Defect Elimination Champion — verify investigation quality, guide reporting practices, and identify systemic improvement opportunities.
• Act as a subject matter expert, offering high-level technical guidance to engineering teams, particularly within condition monitoring and lubrication, to drive strategic alignment and ensure the adoption of industry best practices.
• Lead or contribute to major reliability projects, including strategy creation, updates, and document development.
• Drive the adoption of AI tools to improve effectiveness and automate reliability processes, freeing up engineers from data input, reporting and analysis to more value adding work by using the data to help make key decisions.