At a Glance
- Tasks: Design and maintain automated systems for exploration data, ensuring quality and readiness for AI.
- Company: Endeavour Mining, a leader in the mining industry focused on innovation.
- Benefits: Long-term contract with opportunities for professional growth and development.
- Other info: Collaborative environment with a focus on cutting-edge technology and data-driven decision making.
- Why this job: Join a dynamic team to revolutionise exploration data management and make a real impact.
- Qualifications: Master’s degree in a technical field; experience in data engineering and geoscience preferred.
The predicted salary is between 50000 - 65000 € per year.
As part of its Exploration Strategy, Endeavour Mining is strengthening its enterprise management of exploration and geoscience data to accelerate discovery, improve decision quality, and enable advanced analytics and AI. The Geoscience Data & Automation Engineer plays a critical role in industrializing exploration data flows across all sites. The position is accountable for designing and maintaining automated systems, data transformation, and quality control pipelines for drilling, logging, sampling, assay, survey, and geospatial datasets. The objective is to eliminate manual uploads, spreadsheet dependency, and fragmented QA/QC processes, while ensuring that exploration data is structured, historised, reliable, and analytics ready. The role contributes directly to AI-readiness by enabling clean, standardized, and scalable exploration datasets to be consumed by geological modelling, analytics, and machine learning initiatives.
KEY ACCOUNTABILITIES
- Exploration Data Ingestion & Automation: Design, build, and maintain end-to-end automated data exchanges for exploration systems, including drilling and logging systems (e.g., LogChief, IMDEX), assay laboratory datasets (CSV, XML, API based feeds), BoxScan imaging datasets, survey and geospatial datasets, and Central Geoscience Data Management Systems (GDMS). Ensure secure, scalable, and reliable data flows from field systems to the enterprise data platform. Reduce manual handling and eliminate duplicate or inconsistent data uploads.
- Data Transformation & Historisation: Implement transformation logic to standardise, harmonise, and historise exploration datasets. Ensure data models support longitudinal analysis, geological interpretation, and AI-driven use cases. Maintain clear separation between raw, curated, and analytics-ready datasets.
- Data Quality & QA/QC Automation: Design and implement automated QA/QC checks across exploration datasets, including drillhole validation rules, assay consistency checks, referential integrity controls, schema validation, and completeness checks. Monitor data quality metrics and collaborate with site geologists and QA/QC managers to resolve data issues. Ensure datasets are certified before use in resource modelling or advanced analytics.
- Systems Integration & Architecture: Collaborate with Enterprise Architecture and Data Platform teams to integrate exploration systems with the central data platform. Ensure metadata, lineage, and documentation standards are respected. Design scalable and resilient data pipelines, implement monitoring, logging, and incident resolution mechanisms, and support hybrid architectures where required (site systems + cloud platform).
- Data Capture, Validation & Quality Assurance: Design and supervise data capture workflows from field to system: site geologists, samplers, contractors. Implement automated QA/QC processes to ensure data accuracy, completeness, and consistency. Coordinate with Regional Exploration QA/QC Managers, Site Data Stewards / Field Geologists, GIS Geologists, to ensure data is validated at each stage before use in interpretation or modelling.
- Collaboration & Stakeholder Enablement: Work closely with site geologists and data stewards, Regional Exploration QA/QC Managers, GIS geologists, Data Scientists, and Data Engineers.
SKILLS, KNOWLEDGE & EXPERIENCE
- Education: Master’s degree in computer science, Data Engineering, Information Systems, or a related technical field. Exposure to geoscience or mining domain is highly desirable.
- Exploration Data & Domain Knowledge: Strong understanding of exploration data workflows, including drilling, logging, assays, and survey data. Familiarity with drillhole data structures and QA/QC processes. Exposure to exploration systems such as GDMS, LogChief, IMDEX, BoxScan, or similar platforms.
- Data Engineering & Automation: Proven experience designing and maintaining ETL/ELT pipelines. Strong scripting capabilities (Python preferred). Experience handling heterogeneous data formats (CSV, XML, JSON, APIs). Experience implementing batch and incremental ingestion patterns. Understanding of data transformation, standardisation, and historisation techniques.
- Data Quality & Governance: Experience implementing validation rules and automated data quality frameworks. Understanding referential integrity and structured data models. Familiarity with metadata management and data lineage principles. Ability to balance governance controls with operational usability.
- Cloud & Platform Experience: Experience with enterprise data platforms (cloud preferred). Understanding of orchestration tools and pipeline monitoring. Familiarity with security, access control, and secure data transfer protocols (SFTP, APIs, token based authentication).
- Personal Competencies: Strong analytical and problem-solving mindset. Structured, detail-oriented, and quality-driven. Ability to work across IT and Exploration stakeholders. Capable of managing multiple priorities in a transformation environment. Proactive and solution-oriented, with a strong ownership mindset.
TYPE OF CONTRACT: LONG TERM
Geoscience Data & Automation Engineer in London employer: Endeavour Mining
Endeavour Mining is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Geoscience Data & Automation Engineer role. With a strong commitment to employee growth, we offer opportunities for professional development in a dynamic environment focused on advanced analytics and AI. Our location provides unique advantages, including access to cutting-edge technology and a supportive team dedicated to transforming exploration data management.
StudySmarter Expert Advice🤫
We think this is how you could land Geoscience Data & Automation Engineer in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the geoscience and data engineering fields. Attend industry events, join relevant online forums, and don’t be shy to reach out on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to data automation and exploration systems. Whether it’s a GitHub repository or a personal website, having tangible examples of your work can really set you apart from the competition.
✨Tip Number 3
Prepare for interviews by diving deep into the company’s mission and values. For a role like Geoscience Data & Automation Engineer, understand their exploration strategy and how your skills can contribute to their goals. Tailor your responses to show you’re not just a fit for the role, but for the company culture too!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of resources to help you along the way. Plus, applying directly shows your enthusiasm and commitment to joining our team. Let’s get you that dream job!
We think you need these skills to ace Geoscience Data & Automation Engineer in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with exploration data workflows and automation. We want to see how your skills align with the role of Geoscience Data & Automation Engineer, so don’t hold back!
Showcase Your Technical Skills:Don’t forget to mention your experience with ETL/ELT pipelines and any scripting languages you’re proficient in, especially Python. We’re keen on seeing how you can contribute to our data transformation and quality control processes.
Highlight Collaboration Experience:Since this role involves working closely with various stakeholders, share examples of how you’ve successfully collaborated with geologists, data scientists, or QA/QC managers in the past. We love a team player!
Apply Through Our Website:For the best chance of getting noticed, make sure to apply directly through our website. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Endeavour Mining
✨Know Your Data Inside Out
Make sure you have a solid understanding of exploration data workflows, especially drilling, logging, and assay data. Brush up on the specific systems mentioned in the job description, like GDMS and LogChief, so you can confidently discuss how your experience aligns with their needs.
✨Showcase Your Automation Skills
Be prepared to talk about your experience designing and maintaining ETL/ELT pipelines. Highlight any projects where you've implemented automated QA/QC processes or worked with different data formats like CSV, XML, or APIs. This will demonstrate your technical prowess and relevance to the role.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical and problem-solving skills. Think of examples from your past work where you tackled data quality issues or improved data flows. Use the STAR method (Situation, Task, Action, Result) to structure your answers clearly.
✨Collaborate Like a Pro
Since this role involves working closely with various stakeholders, be ready to discuss your collaboration experiences. Share examples of how you've worked with geologists, data scientists, or QA/QC managers to ensure data accuracy and completeness. This shows you're a team player who can bridge the gap between IT and exploration.
