Join a fast-paced health tech initiative driving data-led transformation in healthcare. We are seeking a Business Intelligence Analyst with a sharp eye for data visualisation and a passion for turning complex information into accessible insights.
In this role, you’ll be more than just a dashboard builder—you’ll be a critical connector between data, policy, and action. You’ll work closely with both data producers and consumers to ensure the right information is available, accurate, and impactful.
What You’ll Do
- Collaborate with multiple policy, planning, and analytics teams to gather, understand, and translate business needs into data visualisation solutions.
- Build interactive dashboards and data products—primarily using Tableau —that enable self-service analytics and drive decision-making.
- Ensure completeness and quality of data through iterative analysis and validation across sources and systems.
- Work hand-in-hand with both upstream (data providers) and downstream (policy users) stakeholders to strengthen data pipelines and usability.
- Interpret data to reveal trends and insights that support healthcare program evaluation, planning, and improvement.
- Help establish and maintain data standards, including adherence to privacy and protection regulations.
- Contribute to an agile, cross-functional team alongside engineers, analysts, and program leads.
What You Bring
Must-Have Skills
- Proficiency in data modelling and visualisation , especially using Tableau .
- Working knowledge of healthcare data , particularly patient journeys in outpatient and GP clinic settings.
- Experience with O365 tools and working in Agile teams.
- High attention to data sensitivity and privacy, with a clear understanding of personal data protection laws.
- Strong interpersonal skills and a proven ability to build trust with both technical and non-technical stakeholders.
Nice-to-Have Skills
- Experience using Python for data wrangling or automation.
- Familiarity with AWS Data Pipeline services.
- Exposure to predictive analytics .
- Appreciation for design principles in data visualisation (e.g., Edward Tufte's The Visual Display of Quantitative Information ).