Build and maintain data products, models, pipelines, dashboards, and reporting solutions across the full data lifecycle. Transform structured and semi-structured data, ensure data quality and governance, define KPI frameworks, and collaborate with engineering, architecture, and business stakeholders. The role uses Azure, Databricks, SQL, and Power BI to deliver trusted datasets for analytics and machine learning.
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.
- 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).
- 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
We offer*:
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
*not applicable for freelancers
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