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Workman LLP

Data Analyst

Workman LLP

. Oversee delivery of data solutions by extracting, cleansing, and transforming data from property management and financial platforms .

Posted 11/11/2026full-timeLondon • United KingdomJuniorMid-Level💰 £38,000 - £45,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data extraction, cleansing, and transformation, with strong capabilities in SQL, Python, and Power BI for delivering actionable insights. Proven ability to manage data solutions and collaborate effectively with stakeholders to enhance operational efficiency.

Highest-signal resume keywords
Strong SQL SkillsPower BI Dashboard DevelopmentData Analysis and ReportingMicrosoft Fabric KnowledgeAdvanced Excel Skills

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data ExtractionData CleansingData TransformationSQL Query OptimizationPython ProgrammingPower BIDAXData WarehousingSemantic ModelsAnalytical Thinking
Soft Skills
Attention to DetailCommunication SkillsCollaborative TeamworkStakeholder Relationship BuildingProject Ownership
Tools & Technologies
Power BIMicrosoft FabricData WarehousesLakehousesExcel
Industry Keywords
Data AnalyticsProperty ManagementFinancial PlatformsOperational EfficiencyCommercial Property Sector

Tech Stack

Tools & technologies
PythonSQL

About the role

Key responsibilities & impact
  • Oversee delivery of data solutions by extracting, cleansing, and transforming data from property management and financial platforms
  • Ensure data is accurate, reliable, and accessible for reporting and analysis
  • Scope and deliver data-driven solutions that improve operational efficiency and reduce manual reporting
  • Analyse large and complex datasets to identify trends, anomalies, and opportunities
  • Translate findings into clear, actionable recommendations for technical and non-technical audiences
  • Build and maintain Power BI dashboards and reports for key business metrics
  • Create and manage structured datasets, semantic models, and reusable query logic
  • Support development of Microsoft Fabric solutions, including data warehouses, Lakehouses, and semantic models
  • Contribute to data standards, documentation, and governance processes
  • Participate in knowledge sharing, peer reviews, and collaborative problem solving
  • Monitor data analytics technology developments and recommend innovative approaches
  • Collaborate with Property Management, Accounts, Building Consultancy, and other service lines

Requirements

What you’ll need
  • 2–3 years' experience in a Data Analyst or similar data-focused role
  • Proven track record of delivering analytical outputs that support business decisions
  • Strong SQL skills, including writing, optimising, and troubleshooting queries against relational databases
  • Solid working knowledge of Python
  • Hands-on experience using Power BI, including DAX
  • Advanced Excel skills for reporting, analysis, and dashboard creation
  • Experience with semantic models and centralised data platforms advantageous
  • Knowledge of Microsoft Fabric highly desirable, including OneLake, Data Warehouses, Lakehouses, pipelines, shortcuts, and semantic models
  • Exceptional attention to detail and strong analytical thinking
  • Ability to manage multiple priorities while maintaining accuracy and delivery standards
  • Strong communication and collaborative teamwork skills
  • Ability to build relationships with stakeholders at all levels and take ownership of projects
  • Willingness to learn, adapt, and contribute to a growing analytics function
  • Interest in the commercial property sector beneficial

Benefits

Comp & perks
  • Hybrid working with a minimum of three days in the office
  • Core working hours
  • Study support
  • Discretionary annual bonus and salary reviews
  • Healthcare, life insurance and wellness programme
  • Long service additional holidays
  • Birthday off
  • Extra day between Christmas and New Year
  • Lifestyle benefits including gym membership, cycle to work, and buy and sell holiday
  • Social events throughout the year including a firm-wide Christmas party
  • Generous referral bonus