Step into a hands-on Data Engineer role at the centre of building a modern, trusted data environment that underpins enterprise decision making.
You will play a critical role in transforming fragmented and inconsistent data into high quality, analytics ready assets, directly enabling reporting, insights and strategic outcomes across the business.
Working within and contributing to established architecture, governance and platform standards, you’ll take ownership of end-to-end data solutions while collaborating closely with stakeholders to ensure data is reliable, secure and aligned to business needs and analytical consumption patterns.
Beyond pipeline development, this role extends into data modelling, analytical enablement and platform design, requiring an engineer who can shape how data is structured, understood and consumed, not just how it is moved.
Success in this role will see you delivering scalable, well governed data pipelines and models that drive confidence in data and unlock tangible business value.
- End-to-end ownership of data solutions. Design, build and operate ingestion, transformation and orchestration pipelines, while applying modern data engineering patterns across batch, streaming and event-driven architectures where appropriate.
- Shape high quality, analytics ready data, develop and maintain curated data models aligned to business definitions, embedding strong data quality, lineage, governance and security practices.
- Drive continuous improvement and engineering excellence, optimise ELT/ETL patterns, enhance scalability and cost efficiency, and proactively resolve complex data issues through root cause analysis and preventative controls.
- Deliver impact through stakeholder partnership, work closely with data owners, governance and business stakeholders to translate requirements into practical solutions that support reporting, analytics and decision making.
- Contribute to data modelling and semantic design, developing dimensional and analytical models that support reporting, self-service analytics and downstream consumption patterns.
- Apply technical data analysis and profiling techniques to understand source systems, validate transformations and support data discovery during solution design.
- Work across modern data platforms (e.g. Azure, Fabric and beyond), applying portable engineering patterns and avoiding vendor lock-in through well-designed abstractions and standards.
