Principal Data Analytics — Reliability & Asset Insights Lead

BHP; City of Melbourne; On-site; AUD 180,000 - 280,000; Full time

Benefits offered by this job

Performance-based bonuses

Employee share program

Flexible working options

Job summary

BHP is seeking a Principal Data Analytics professional to guide the technical and analytical direction of the maintenance portfolio. You will quantify trade-offs between reliability, cost and risk and lead production-ready analytics solutions.

You will design data models and pipelines, define analytics standards, and ensure findings drive action with senior stakeholders. Collaborative work with data scientists, analysts and business experts is expected.

Qualifications

• Must have strong SQL and Python skills with production-ready analytics experience.
• Experience designing data models, pipelines and schemas used by practitioners.
• Reliability engineering or asset management experience in mining/manufacturing or heavy industry.
• Ability to develop executive-level narratives and high-quality communication artefacts.
• Strong analytical and creative problem-solving skills.

Responsibilities

• Lead the development of industry-leading maintenance analytics solutions.
• Own end-to-end data models and governed pipelines; set analytics standards.
• Translate findings into real-world action for senior leadership forums.
• Collaborate with data scientists, data analysts and business SMEs.

Skills

SQL

Python

Data modelling

Pipelines

Executive storytelling

Analytical thinking

Problem solving

Spanish (optional)

Education

Relevant tertiary qualification in Engineering, Science, IT

Job description

BHP is seeking a Principal Data Analytics professional to guide the technical and analytical direction of the maintenance portfolio. You will quantify trade-offs between reliability, cost and risk and lead production-ready analytics solutions.

You will design data models and pipelines, define analytics standards, and ensure findings drive action with senior stakeholders. Collaborative work with data scientists, analysts and business experts is expected.