Data Engineer

firstquantum; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

First Quantum Minerals is seeking a senior Data Engineer to design, develop and maintain data pipelines in the Azure cloud. You will work with Data Engineers, DBAs and Data Architects to deliver sustainable, high-performance solutions that power analytics across the business.

The role focuses on automation, CI/CD for pipelines, governance of data and algorithms, and collaboration with the DNA CoE to ensure quality, security and scalable data delivery.

Qualifications

• Advanced SQL knowledge to support existing patterns and services.
• Experience with Azure cloud data platforms and Databricks.
• Ability to differentiate data engineering patterns from integration patterns.

Responsibilities

• Advise architecture enhancements for the Data Engineering Service across Azure Databricks and Azure Data Factory.
• Define and enforce distinctions between data engineering and integration patterns.
• Set the optimisation and automation strategy for the platform and data pipelines.
• Drive end-to-end DevOps and CI/CD for pipelines and releases.
• Collaborate with DNA CoE, DBA and Platform Owner on data governance and quality.

Skills

Azure Databricks

SQL

Data pipelines

DevOps

CI/CD

Tools

Azure Data Factory

Azure DevOps

Git

Job description

Job description:

At First Quantum, we free the talent of our people by taking a very different approach which is underpinned by a very different, very definite culture - the "First Quantum Way". Working with us is not like working anywhere else, which is why we recruit people who will take a bolder, smarter approach to spot opportunities, solve problems and deliver results. Our culture is all about encouraging you to think independently and to challenge convention to deliver the best result. That's how we continue to achieve extraordinary things in extraordinary locations.

Company Description

First Quantum Minerals is a leading Canadian-based global mining & metals company focused on the production of copper, nickel, gold & cobalt. As a company, we strive for continuous excellence and after 25 years of operations we are now 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, and 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.

Job Description

Although our production and financial results are the engine that drives our business, it is the depth of capability in our people that will continue to determine First Quantum's ongoing success. Reporting to the Lead, Group Data Operations, this role will form an integral part of our global D&A function and act as t he technical authority for data engineering at FQM. Work collaboratively within an integrated team of Data Engineering, Data Designers, Data Scientists, Database Administrators, DevOps Engineer and Data Architects, 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. As such, success will be measured not by pipelines built, but by a service that is sustainable, repeatable, performant, and trusted by the business.

What success looks like in year one

• Measurably improved SLAs across the Data Engineering Service.
• Automation and refined processes across DevOps and the Engineering Service.
• The reputation of the Data Engineering Service is demonstrably high within the business.
• Increased data literacy and engineering capability across data operations .
• A strong, functioning relationship with the Centre of Excellence.

Key Responsibilities:

Primary Role

• In collaboration with the Group Data Operations Lead, they will advise architecture enhancement and design engineering patterns for the Data Engineering Service across Azure Databricks and Azure Data Factor y.
• Define and enforce the distinction between data engineering patterns (optimised for fast, large-scale processing) and integration engineering patterns (Azure Integration Services, streaming, alerting, and monitoring), ensuring work is routed to the right discipline.
• Set the optimisation strategy for the platform ... caching, indexing, partitioning, and cost .
• Drive automation through the data engineering delivery lifecycle so that repeatable work is engineered out and not bloat MSP uptime.
• The role will have advanced SQL knowledge to continue delivery of pre-existing patterns and collaborate with DBA and Platform Owner from DNA CoE.

Quality, DevOps and release

• Act as the engineering quality gate: review MSP and internal code before main branch and to 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. DevOps represents a key skill to be deployed in this role.
• P rogressively delegate review and release responsibility to the Data Engineer, with structured handover targeted across years two and three.

Governance and data management

• Establish and maintain the governance of data and algorithms used for analysis, analytical applications, and automated decision-making within the engineering estate.
• Take accountability for exploiting the value from our target systems, data delivered must be 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 a