Business Intelligence - Data Analyst

About the role

We are looking for a detail‑oriented Business Intelligence Data Analyst with solid experience in the real‑estate sector. You will turn complex property, transaction and market data into actionable insights that support strategic and operational decisions across the organization.

Key responsibilities

• Collect, clean, validate and maintain real‑estate data from internal and external sources.
• Analyze property, transaction, client and market data to identify trends and support business decisions.
• Develop and maintain dashboards, reports and KPIs for leadership and operational teams.
• Ensure data integrity, consistency and accuracy across CRM systems, MLS databases and other platforms.
• Perform data audits, resolve discrepancies and improve data quality.
• Support forecasting, pricing analysis, pipeline tracking and performance reporting.
• Collaborate with operations, sales, acquisitions, property management and executive teams.
• Automate recurring reports and optimise data workflows.
• Document data processes and uphold data‑governance standards.
• Monitor market trends and provide analytical support for strategic initiatives.

Required profile

• 3+ years as a Data Analyst, Business Analyst or similar role.
• At least 2 years working with real‑estate data (property, MLS, CRM, portfolio).
• Strong analytical, problem‑solving and critical‑thinking abilities.
• Excellent attention to detail and data accuracy.
• Fluent written and verbal communication in English.

Required skills

• Advanced Microsoft Excel (Pivot Tables, Power Query, complex formulas).
• SQL for querying and managing databases.
• Dashboard creation with Power BI, Tableau or Looker Studio.
• Experience with CRM platforms such as Salesforce, HubSpot, Follow Up Boss, Propertybase, AppFolio or Buildium.
• Familiarity with MLS systems and real‑estate transaction workflows.
• Python or R for data analysis and automation.
• ETL processes and data‑warehousing concepts.
• API integration and handling multiple data sources.