Senior Analytics Engineer

You will join a global Data & Analytics team serving one of the world's top 10 copper producers, operating across Africa, Europe, the Middle East, Australia, and the Americas. The team is on a mission to build a world-class data platform that turns raw operational data into strategic insight - enabling leadership to make faster, smarter decisions at every level of the business.

As an Analytics Engineer you will sit at the intersection of data engineering and business intelligence - modelling, transforming, and publishing clean, tested, and reusable datasets that power dashboards, predictive models, and KPI frameworks across the organisation.

Responsibilities:

• Design and build data products across the full data lifecycle - from ingestion through transformation to serving.
• Develop robust, well-documented data models in close collaboration with business users, data engineers, and analytics architects.
• Extract, transform, and validate data from diverse sources including JSON & XML feeds, leveraging strong metadata management practices.
• Deliver clean, tested, code-reviewed datasets and data pipelines ready for analysis and machine-learning consumption.
• Partner with senior stakeholders to define KPI frameworks, reporting standards, and data governance best practices.
• Collaborate with data engineers to enrich product design and integrate data for predictive models.
• Create and maintain dashboards and reporting solutions using PowerBI to enable data-driven decision-making.
• Evaluate and recommend improvements to data flows, influencing platform architects and engineers.
• Implement data validation, monitoring, and error-handling processes to ensure data quality and accuracy.
• Maintain high-quality documentation including data dictionaries and lineage artefacts.

Requirements:

• 8+ years of experience in data analytics, data engineering, or a closely related software engineering discipline.
• Strong SQL skills for data extraction and manipulation; deep expertise in data modelling and indexing strategies.
• Solid hands-on experience with Azure cloud services for data storage and processing (Azure Data Lake, Azure Synapse Analytics, or equivalent).
• Proficiency in Databricks for data product building and large-scale data transformation.
• Experience transforming and working with semi-structured data formats (JSON, XML).
• Solid understanding of data governance, data quality principles, and security best practices.
• Strong analytical and problem-solving skills with an ability to work independently in a fast-paced environment.
• Excellent communication skills – able to present findings and data insights to both technical and non-technical audiences.
• Master's degree in Computer Science, Data Science, Software Engineering, or a related field (or equivalent professional experience).

Nice to have:

• Experience with alternate cloud providers (AWS, GCP) in addition to Azure.
• Background in mining, commodities, or heavy industry operational data.
• Proficiency in additional languages beyond English