Analytics Engineer II

Purpose Statement

We're looking for a technically versatile Analytics Engineer to sit at the intersection of data engineering and data analysis — To bridge the gap between Data Engineers and Data Analysts by transforming complex data into accessible, reliable and performant data models and insights that drive decision-making across the organisation. You'll collaborate with stakeholders to understand analytical needs, partner with Data Architects and Data Modellers to design scalable models, and build the efficient, reproducible data assets — including data models and marts, semantic layers and working environments — along with the transformations and pipelines that let analysts deliver insights with speed, consistency and minimal frictionat a time when both worlds are running side by side. The team is migrating to a modernised data platform while keeping the legacy environment live. You'll make sure the data stays clean, reliable and accessible across both — and that no one on either side of the transition feels the friction.

What you'll do

• Build scalable data models, marts and semantic layers


• Design reproducible transformations and pipelines across legacy and modernised environments


• Partner with Data Architects and Data Modellers to align on enterprise data strategy


• Maintain data quality and governance standards throughout the migration


• Productionise reports using engineering principles


• Work with CI/CD pipelines, testing frameworks and orchestration tools like Airflow3


• Use AI tools — including Copilot and Claude — as active partners in your work 

Minimum Experience

• Honours degree in an analytics/engineering or STEM or related field, PLUS at least 5yrs relevant experience OR


• Bachelor’s degree in an analytics or STEM or related field, PLUS at least 8yrs relevant experience OR  


• Equivalent experience of 8 yrs relevant experience and/or relevant certifications.


• At least 5 years’ experience in analytics engineering or a related role


• Proven track record of delivering scalable data solutions and leading projects


• Experience with high-volume data environments 


• Experience with CI/CD, testing frameworks and orchestration tools (e.g., Airflow)


• Experience productionising reports using engineering principles 

Qualifications (Minimum)

Qualifications (Ideal or Preferred)

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).

Conditions of Employment