Requirements
- Bachelor's degree in Data Science, Statistics, Information Systems, Computer Science, or a related quantitative field.
- 5 to 7 years of experience in a BI analyst, data analyst, or closely related analytics role, with at least 2 to 3 years operating at a senior level.
- Demonstrated track record of building and maintaining dashboards and automated reports that are actively used by non-technical stakeholders across an organisation.
- Proven experience operating in an internal-services or business-partnering model, serving multiple teams or business units with different and competing data needs simultaneously.
- Comfortable working with impact metrics and performance data in a programme or delivery context, with the ability to translate operational data into meaningful organisational insights.
- Demonstrated contribution to data literacy and self-service adoption within an organisation, through training, documentation, or tooling improvements that measurably improved how teams use data.
- Strong SQL proficiency, including the ability to write complex queries against cloud data warehouse environments.
- Hands-on experience with at least one major BI tool such as Metabase, Superset, Tableau, or Power BI.
- Familiarity with cloud data warehouse environments such as ClickHouse, BigQuery, or Redshift.
- Experience consuming dbt-modelled data and working within a semantic layer.
- Strong data visualisation design skills with the ability to produce dashboards that are intuitive and appropriately tailored to their audience.
- Comfort with descriptive statistics and the ability to apply basic statistical reasoning to operational and organisational data.
- Data quality awareness, including the ability to identify inconsistencies, interrogate data pipelines, and flag issues to the Analytics Engineer.
- Proficiency in Google Sheets or Excel for stakeholder-facing data work.
Nice to Have
- Postgraduate qualification is preferred but not required. Demonstrated practical experience is weighted equally to formal credentials.
- Python or R for ad-hoc analysis and reporting automation is preferred but not required.
- Familiarity with version control using Git for managing BI assets and documentation is preferred but not required.
