Analytics Engineer

Build trusted data on our new Databricks platform, shape enterprise analytics and help transform reporting through modern AI-enabled ways of working.

• Build our new enterprise data platform
• Shape trusted data for reporting and AI
• Modernise analytics with Databricks and AI

Ngā kōrero mō te tūranga – About the role

Help shape how the University of Waikato uses data to support better decisions, reporting and insight. Play a central role in building our new enterprise data platform using Databricks. This is a key role at the intersection of data engineering, analytics and business analysis, turning source data into trusted, well-modelled and business-ready datasets. You will work with stakeholders across the University to understand reporting and insight needs, agree the definitions of entities, measures and business terms, and translate these into canonical and dimensional data models. You will also develop the governed semantic layer and business context that sit behind Power BI, Databricks dashboards and natural-language analytics such as Genie. A significant part of the role will be helping migrate reporting and datasets from our legacy data warehouse to the modern platform. You will rebuild existing reporting logic to current standards, rather than simply replicate legacy approaches, ensuring the resulting data is consistent, tested, documented and trusted. This is an opportunity to help establish modern analytics engineering practice within a new enterprise data platform, including the practical use of AI-assisted and agentic ways of working. Salary will be provided based on skills, knowledge and experience brought to the position. This is a full-time role (37.5 hours a week), based in Hamilton.

Ko wai koe? – Who are you?

You will bring experience in analytics engineering, business intelligence, data modelling, business analysis or a similar data-focused role. While the title Analytics Engineer may be less familiar in New Zealand, we are keen to hear from experienced BI Developers, Data Modellers and Senior Data Analysts who have the right transferable skills.

• At least three years’ relevant experience in analytics engineering, BI, data modelling, business analysis or a related data role.
• Strong SQL skills and solid knowledge of dimensional modelling, including facts, dimensions and star schemas.
• Experience building semantic models or governed measures in platforms such as Power BI.
• Experience applying DataOps practices, such as version control and the structured promotion of code between environments.
• Strong requirements-gathering and stakeholder engagement skills, with the ability to agree data definitions and communicate data concepts clearly to technical and non-technical audiences.
• Openness to, and practical use of, AI-assisted development tools.