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About the Role

This role will form an integral part of our global D&A function and act as the technical authority for data engineering at FQM. Work collaboratively within an integrated team, this role will be responsible for designing, developing, and maintaining data pipelines and systems in the Azure cloud environment, ensuring the smooth deployment and vigilant monitoring of data solutions. Success will be measured by a service that is sustainable, repeatable, performant, and trusted by the business.

Responsibilities

• Advise architecture enhancement and design engineering patterns for the Data Engineering Service across Azure Databricks and Azure Data Factory.
• Define and enforce the distinction between data engineering patterns and integration engineering patterns.
• Set the optimisation strategy for the platform including caching, indexing, partitioning, and cost.
• Drive automation through the data engineering delivery lifecycle.
• Utilize advanced SQL knowledge to continue delivery of pre-existing patterns and collaborate with DBA and Platform Owner from DNA CoE.
• Act as the engineering quality gate: review MSP and internal code before main branch and own the definition of done for data engineering and Integration work.
• Own the DevOps practice end to end, focusing on CI/CD for pipelines, environment promotion, branching standards, DevOps ceremony, and release governance.
• Progressively delegate review and release responsibility to the Data Engineer.
• Establish and maintain the governance of data and algorithms used for analysis, analytical applications, and automated decision-making.
• Take accountability for exploiting the value from target systems, ensuring data delivered is repeatable, accurate to its use case, and designed effectively for the platform.
• Collaborate with analytics engineering and data science to uphold data quality, security, and governance.
• Act as the technical SME across data engineering disciplines.
• Mentor engineers and create and promote best practice.
• Raise data literacy and engineering capability across the data operations.
• Communicate clearly with business stakeholders.
• Context-switch across multiple concurrent lines of work while remaining accountable for each.
• Build and maintain a strong working relationship with the Centre of Excellence.
• Hold the MSP to the engineering standard, improving Data Engineering Service SLAs year on year.

Requirements

• At least six years in data management disciplines — data integration, modelling, optimisation, and data quality — with proven delivery of modern cloud data platforms.
• Demonstrated experience leading engineering quality in a multi-supplier or managed-service environment.
• Mining, heavy industry, or comparable industrial experience is valuable.
• Expert SQL, query optimisation, indexing strategy, and performance diagnosis.
• Expert DevOps capability; CI/CD, release management, environment strategy, and engineering ceremony discipline.
• Proven experience extracting data from vendor and operational APIs, handling authentication schemes (OAuth2), pagination, rate limits, and schema drift.
• Fundamental excellence in Azure Data Factory, including metadata-driven and parameterised pipeline design.
• Strong development capability in Databricks and Spark, with working command of Unity Catalog, Delta Lake, and the medallion architecture.
• Strong understanding of IoT and telemetry data - high-volume, high-frequency operational data from industrial sources.
• Strong understanding of data governance and orchestration.
• Clear command of engineering versus integration patterns, and when each applies.
• Experience with complex data types, spatial data desirable.
• Exposure to Databricks, Synapse, Power BI.
• Performance and results orientated.
• Proficiency in navigating change within an evolving environment.
• Capability to perform effectively in high-pressure situations.
• A standard setter against their code, review discipline, and documentation become the benchmark others work to.
• Passionate about efficiency & energised by developing junior engineers.
• A strong, plain-spoken communicator, able to translate between executive, business, and technical audiences.
• Comfortable holding a supplier to account constructively and holding a line on quality.

Skills

• Data Engineering
• Data Design
• Data Science
• Database Administration
• DevOps Engineering
• Data Architecture
• Azure Cloud
• Azure Databricks
• Azure Data Factory
• SQL
• CI/CD
• API Integration
• OAuth2
• Spark
• Unity Catalog
• Delta Lake
• Medallion Architecture
• IoT
• Telemetry Data
• Data Governance
• Orchestration
• Spatial Data
• Synapse
• Power BI

Location

• London, UK

Work Type

• Hybrid

Experience Level

• At least six years in data management disciplines

About the Company

• First Quantum Minerals is a leading Canadian-based global mining & metals company focused on the production of copper, nickel, gold & cobalt.
• After 25 years of operations, we are one of the world’s top 10 copper producers, exporting millions of tonnes of concentrate from multiple countries to customers worldwide.
• Our operations and future developments span across Africa, Europe, the Middle East, Australia and the Americas.
• We are globally recognised for our specialist technical, engineering, construction and operational skills, which allow us to unlock value from complex mineral projects and deliver rewarding careers for our people, returns for our shareholders and sustainable development for the many local communities that host our operations.
• As we expand our operations, continue to provide metals to build the modern world and shift to a low carbon, greener economy in the years ahead, our mining projects will continue to require the best and the brightest talent to help us solve the emerging challenges of our time, shape our business and unlock opportunities for our future.