Analytics engineer ii_pipeline
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
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