We need this role because reliable analytics depend on well‑designed, well‑tested data foundations. We turn raw, complex data into structured, business‑ready datasets that teams can trust every day. This role exists to ensure data models, pipelines and semantic layers are built to perform, scale and support meaningful decision‑making across the business.
What you’ll do
- Design, build and maintain production‑ready data models that transform raw data into usable datasets
- Develop scalable data transformations with strong validation, testing and quality controls
- Create and optimise semantic layers and aggregation logic that support reporting and analysis
- Maintain and troubleshoot live data models, resolving incidents and improving performance
- Lead and influence design decisions, balancing quality, speed and long‑term sustainability
- Support and guide less experienced engineers through reviews, documentation and practical coaching
The team and how work gets done
We work at the point where data becomes usable. The focus is on structuring, modelling and supporting data that feeds reporting and insights across multiple teams. Collaboration is key, with regular engagement across engineering, analytics and architecture. The work directly affects how quickly questions can be answered and how confidently decisions can be made.
What we’re looking for
- At least 5 years' experience in analytics engineering or a closely related data role
- Proven experience delivering and supporting production data models and pipelines
- Strong data modelling capability and confidence designing business‑ready datasets
- Advanced SQL skills and experience using Python for data transformation or automation
- Experience building, testing and deploying data transformations using structured release practices
- Experience working on cloud data platforms and workflow orchestration tools such as Airflow or Prefect
- A solid understanding of data quality, governance and documentation
- Experience influencing technical decisions and working closely with stakeholders
- A bachelor’s degree in analytics, data, engineering, STEM or a related field
Minimum Qualifications
- Bachelor's Degree in Analytical/Data/Technical or Other
Preferred Qualifications
- Honours Degree in Analytical/Data/Technical or Engineering - Other
Knowledge
- Advanced grasp of data modelling best practices
- Data governance and quality assurance
- Cloud data platforms and orchestration tools (E.g., Airflow, Prefect)
- Understanding of software engineering principles (E.g., CI/CD, testing)
Skills
- Analytical Skills
- Communication Skills
- Planning, organising and coordination skills
- Problem solving skills
- Reporting Skills
Conditions of Employment
- Clear criminal and credit record