Reliability Engineer – Underground Mining, Otago NZ

OceanaGold Corporation; New Zealand; On-site; NZD 120,000 - 170,000; Full time

Benefits offered by this job

Residential Otago NZ role

Competitive salary + bonus structure

Retail and services discounts

Free Southern Cross healthcare

Monthly health allowance

Living Our Values recognition

Onsite physiotherapist and nurses'uite

Free transport to work

Job summary

OceanaGold Corporation is seeking a capable Reliability Engineer for the Macraes underground mining department in Otago, NZ. You will own and optimise asset strategies for the mobile fleet, analyse performance data, and drive reliability and safety improvements to create value and sustainability.

The role reports to the Maintenance Superintendent and is a key driver of reliability performance, defect elimination, and data-driven decision-making.

Qualifications

• 3+ years experience working with data.
• 3+ years experience in a maintenance reliability role in mining or related heavy industry.

Responsibilities

• Lead asset criticality assessments and mitigation strategies.
• Develop maintenance strategies including intervals and spares.
• Configure and maintain master data in Pronto CMMS.
• Analyse performance data and generate structured reports.
• Lead defect elimination and continuous improvement initiatives.
• Monitor asset condition and recommend corrective maintenance.
• Report using fleet management data and Pronto data.
• Lead Root Cause Analysis of losses or near-misses.

Skills

Data analysis

Reliability engineering

Mining industry experience

Education

Engineering degree

Tools

Pronto CMMS

Job description

OceanaGold Corporation is seeking a capable Reliability Engineer for the Macraes underground mining department in Otago, NZ. You will own and optimise asset strategies for the mobile fleet, analyse performance data, and drive reliability and safety improvements to create value and sustainability.

The role reports to the Maintenance Superintendent and is a key driver of reliability performance, defect elimination, and data-driven decision-making.