This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Geological Data Consultant based in Australia.
This is a hands-on consulting role focused on improving the quality, reliability, and usability of geological and mining-related data across a diverse portfolio of projects. You will work directly with complex real-world datasets, ensuring they are structured, validated, and fit for technical reporting and decision-making. The role combines technical data expertise with consulting engagement, requiring close collaboration with both internal teams and external clients. You will play a key part in identifying data issues, improving workflows, and implementing practical solutions that enhance efficiency and consistency. Operating in a dynamic and flexible consulting environment, you will also leverage modern tools, including automation and AI-assisted approaches, to strengthen data processes. This position is ideal for a pragmatic, detail-oriented professional who thrives in problem-solving environments and enjoys working with imperfect but high-value datasets.
Accountabilities
- Manage, validate, and maintain geological and geoscientific datasets across mining, exploration, and environmental projects.
- Administer and support relational databases, ensuring data integrity, accuracy, security, and optimal performance.
- Perform data QA/QC processes, including cleaning, validation, and preparation for reporting and downstream technical analysis.
- Integrate and assess public and government datasets (e.g., WAMEX and equivalent sources) for reconciliation and validation purposes.
- Support data migrations, system upgrades, and continuous improvement initiatives across data platforms and workflows.
- Identify, troubleshoot, and resolve data inconsistencies using structured and pragmatic problem-solving approaches.
- Collaborate with internal stakeholders and clients to clarify requirements, resolve data-related queries, and ensure timely delivery.
- Contribute to the improvement of data standards, processes, and automation opportunities to enhance efficiency and scalability.
- Ensure data outputs are reliable, well-documented, and suitable for technical interpretation and reporting needs.
- Apply sound judgement when working with incomplete or evolving datasets in fast-paced consulting environments.
Requirements
- Experience working with geological or geoscientific data within mining, exploration, or environmental contexts.
- Strong proficiency in relational databases and SQL for data validation, querying, and troubleshooting.
- Hands-on experience with data management, QA/QC processes, and ensuring data quality in technical environments.
- Familiarity with geological data systems or platforms, with the ability to quickly adapt to new tools and technologies.
- Experience working with large, complex, or imperfect datasets and maintaining accuracy under ambiguity.
- Strong analytical and problem-solving skills with a practical, solution-oriented mindset.
- Excellent communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.
- Strong organisational and self-management skills, with the ability to handle multiple priorities independently.
- GIS experience is highly desirable for spatial validation and geoscientific analysis.
- Exposure to environmental datasets or regulatory data systems is considered an advantage.
- Degree in geology, geoscience, data science, or a related technical field is preferred.
Benefits
- Flexible working arrangements, including full-time, part-time, and hybrid work options.
- Exposure to a wide variety of mining, exploration, and environmental projects across different commodities and clients.
- Opportunity to work on complex, real-world datasets with meaningful technical and operational impact.
- Supportive, trust-based consulting environment with autonomy and responsibility.
- Professional development opportunities through diverse project exposure and continuous learning.
- Collaborative team culture that encourages knowledge sharing and practical problem-solving.
- Opportunity to work with modern data tools, automation techniques, and AI-assisted workflows.
- Strong focus on work-life flexibility and adaptable working arrangements.