Responsibilities
- Act as a primary point of contact for data requests, including reporting, analysis, ad‑hoc queries, and changes to business processes or client set‑ups.
- Deliver timely ad‑hoc reporting and data extracts to internal and external stakeholders, focusing on broker and commercial team requirements.
- Translate business requirements into clear technical specifications and produce reporting solutions using tools such as SSRS and Power BI.
- Support the maintenance and integrity of the Data Warehouse by performing regular checks, identifying issues, and working with relevant teams to resolve them.
- Build strong relationships with the Data Warehouse team to ensure effective, appropriate use of data across the organisation.
- Collaborate with colleagues to automate or streamline data‑related tasks, providing expert support (including advanced Excel usage).
- Proactively identify opportunities to improve data accuracy, consistency and governance.
- Act as a role model for responsible data use, ensuring compliance with regulatory requirements and Healix values.
Required Qualifications
- Previous experience in a Data Analyst or similar analytical role, working with complex datasets.
- Strong Excel skills (including formulas, PivotTables and lookups).
- Working knowledge of SQL for data extraction and analysis.
- Understanding of data protection and information governance, including GDPR and the Data Protection Act 2018.
- Strong analytical and problem‑solving ability, with attention to root cause analysis.
- Ability to manage priorities and deadlines independently.
- High attention to detail and a strong focus on data accuracy.
- A professional, values‑driven approach when handling sensitive information.
Desired Qualifications
- An interest in automation, process improvement or developing analytical best practice.
- Experience within health insurance, trusts, or regulated financial/health environments.
- A mathematical, numerical or analytical academic background.
- Experience producing reports and dashboards using SSRS, Power BI or similar tools.
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