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Sky Network Television in Auckland is seeking a Data & Business Intelligence Analyst to cover a 9‑month fixed term. You will design, build and maintain reporting and analytics solutions, translating business needs into robust data models, dashboards and outputs for informed decision making.
Working across Ad Sales, Insights and Commercial teams, you will write SQL, develop Power BI reports, ensure data accuracy, and support UAT and production releases.
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We have an exciting opportunity for a Data & Business Intelligence Analyst to join our Data, Research and Insights team, proving maternity leave cover for the next 9 months on a fixed term contract. This role supports the design, build and maintenance of reporting and analytics solutions across the business, helping teams turn data into clear, actionable insight.
Working closely with stakeholders in across teams such as Ad Sales, Insights and Commercial teams, you’ll translate business requirements into robust data models, dashboards and reporting outputs that support confident decision making.
This role is ideal for someone who enjoys the full analytics lifecycle — from working with raw data in the warehouse, to modelling it cleanly, validating accuracy, and presenting it in a way that helps the business make better decisions. As part of the wider Research, Data & Insights team, you’ll contribute to reliable, effective reporting and self‑service analytics capability across Rangiata Sky.
Due to the breadth of teams and stakeholders you’ll collaborating with, being flexible to work across both of our Auckland offices (CBD and Mt Wellington) is required.
The ideal candidate will bring experience working with databases, business intelligence tools and analysis, along with proven capability building data transformation pipelines and creating reporting outputs that meet stakeholder needs.
You’ll have strong SQL skills, hands‑on experience building dashboards and data models in Power BI or similar tools, and the ability to communicate technical concepts clearly to non‑technical audiences. Experience with cloud data warehouses such as Snowflake, Databricks or similar, as well as solid understanding of data warehousing concepts and dimensional modelling, will be highly valued.