Analytics Engineer II

Purpose of the role:

The role bridges the gap between Data Engineers and Data Analysts by transforming complex data into accessible, reliable and performant data models and insights that support organisational decision‑making. The Analytics Engineer collaborates with stakeholders to understand analytical needs and partners with Data Architects and Data Modellers to design scalable data models aligned with enterprise data strategy. The role is responsible for designing and building efficient, reproducible data assets. This includes data models, data marts, semantic layers and working environments, as well as scalable transformations and pipelines. These assets enable Analytical Engineers and Data Analysts to deliver insights and reports quickly, consistently and with minimal friction.     

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

Minimum Experience

• At least 5 years’ experience in analytics engineering or a closely related data role
• Honours degree in an analytics/engineering  or STEM  or  related field, PLUS at least 5yrs relevant experience  OR
• Bachelor degree in an analytics or STEM  or  related field, PLUS at least 8yrs relevant experience 
• 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
  
  

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).

Skills

Conditions of Employment