Data Analyst, Power Bi

· Designing, building and maintaining Power BI dashboards and reports for internal teams and client reporting requirements

· Building and optimising data models in Power BI - star schema design, relationships and DAX measures - to ensure accurate and performant reporting

· Writing and optimising SQL queries to extract, join and validate data across multiple source systems

· Preparing and transforming data using Power Query (M) - cleaning, shaping and consolidating inputs from Excel, CSV files, databases and APIs

· Automating recurring reporting through scheduled refreshes, dataflows and gateway configuration in the Power BI Service

· Managing workspaces, publishing, row-level security and user access so that the right stakeholders see the right data

· Working with teams across the firm to gather requirements, define metrics and translate business questions into reporting solutions

· Performing data validation and reconciliation so that reported numbers tie back to source, and investigating variances before reports are released

· Complying with IT policies and procedures

· Maintaining security of information at all times

Requirements

· Power BI - Strong hands-on experience building production dashboards in Power BI Desktop and publishing, scheduling and administering them in the Power BI Service.

· DAX - Ability to write and debug DAX measures, including time intelligence, calculated columns and tables, and issues arising from filter and row context.

· Data Modelling - Sound understanding of dimensional modelling (star schema), relationships and cardinality, and the impact of model design on report performance.

· Power Query / Data Preparation - Proficiency in Power Query (M) for cleaning, shaping and combining data from varied and inconsistent sources.

· SQL - Strong SQL skills for querying relational databases, including joins, aggregations, window functions and basic query tuning.

· Excel - Advanced Excel skills (pivot tables, lookups, Power Pivot) for ad-hoc analysis and reconciliation.

· Visualisation & Reporting Design - Ability to structure a dashboard around the decision it supports - clear layout, appropriate chart selection and consistent formatting.

· Data Quality - Detail-oriented approach to validation and reconciliation, with the discipline to check outputs thoroughly before they reach internal or client-facing use.

· Communication & Collaboration - Good communication skills, with the ability to work across teams and explain data and findings clearly to non-technical stakeholders.