Data Analyst

Data Analyst

Key Responsibilities

1. Reporting & Analysis

• Develop and enhance Power BI dashboards, including new filters, performance optimisations, and UX improvements.
  
• Perform ad-hoc analysis to answer business questions across multiple data sources.
  
• Maintain and optimise existing reports in Excel, SSRS, and Power BI.
  
• Conduct exploratory data analysis to identify trends, patterns, and opportunities.
  
• Support end-of-month finance processes and EDW/IDW operations.
  

2. Data Investigation & Quality

• Investigate and resolve data quality issues using systematic “is/is not” root cause analysis.
  
• Collaborate with engineering teams to identify, document, and resolve discrepancies.
  
• Validate data accuracy across both Fabric and legacy systems.
  
• Provide business users with clarity on data definitions, limitations, and correct usage.
  

3. Self-Service Enablement & Training

• Empower business teams to access data independently via self-service tools.
  
• Provide training and documentation for Power BI and related Fabric capabilities.
  
• Guide tool selection (Excel, Power BI, or other Fabric tools) based on requirements.
  
• Assist in gathering business requirements for vendor-delivered solutions and validate outputs.
  

4. Business Insights & Strategic Support

• Analyse performance metrics to identify improvement opportunities.
  
• Support strategic initiatives with predictive modelling and forecasting (where applicable).
  
• Present actionable insights and recommendations to stakeholders.
  
• Provide data-driven input for business cases and investment decisions.
  

Essential Skills & Experience

• 2+ years

  in business intelligence or data analysis roles.
• Advanced

  Power BI

  skills (dashboard creation, DAX, data modelling, troubleshooting).
• Strong SQL skills for querying and analysis (Fabric & SQL Server).
  
• Experience with

  legacy systems

  : Excel/VBA, SSRS, OLAP Cubes.
• Systematic problem-solving approach (“is/is not” methodology).
  
• Strong communication skills to explain technical issues and guide tool adoption.
  
• Proven experience supporting migrations from legacy to modern analytics platforms.
  

Preferred Skills

• Microsoft certifications (PL-300, DP-600).
  
• Experience with Python, R, or similar analytical languages.
  
• Background in finance, operations, or commercial analysis.
  
• Familiarity with Microsoft Fabric notebooks or Jupyter notebooks.
  
• Statistical analysis or data science knowledge.
  
• Experience training business users on analytics tools.
  

Ways of Working

• Agile/Scrum environment with flexibility for BAU priorities.
  
• Close collaboration within a

  three-role squad

  :

• Data Platform Engineer

  – platform governance & vendor oversight

• Data Engineer

  – data pipelines & gold tables

• Data Analyst

  – business insights & self-service enablement
• Hybrid technology environment (modern cloud + on-premises systems).
  
• Strong vendor coordination responsibilities for data product delivery.
  

Success Metrics

• Improved platform performance and cost optimisation.
  
• High data quality and reliability across reports.
  
• Increased adoption of self-service analytics.
  
• On-time, standards-compliant vendor project delivery.
  
• Measurable progress in migrating users from legacy to modern tools.