Job Title

Senior Data Analyst:

Job Description Summary

Job Description

We are seeking a Data Analyst to support data-driven decision-making across the organization by collecting, cleaning, analyzing, and interpreting large, complex datasets. This role will transform raw data into actionable insights that improve operational efficiency, support strategic initiatives, and identify growth opportunities. Experience in commercial real estate a plus, but not required.
The ideal candidate is highly analytical, curious, comfortable working across multiple data environments, and experienced in turning messy, real-world data from multiple sources into clear, trusted insights through reports, dashboards, and visualizations.

Key Responsibilities:

• Collect, clean, validate, and analyze large datasets from multiple internal and external sources
• Perform data profiling, quality checks, and validation to ensure accuracy and reliability
• Identify trends, patterns, and anomalies through exploratory and statistical analysis
• Translate analytical findings into actionable insights for business stakeholders
• Build and maintain dashboards, reports, and visualizations using tools such as Tableau or Power BI
• Write and optimize queries using SQL to extract and manipulate data from relational databases
• Work with data stored in data lakes, SQL Server databases, and Salesforce
• Support ad hoc analysis and recurring reporting needs across teams
• Collaborate with data engineering, product, research, and business teams to define requirements and ensure alignment
• Document data definitions, assumptions, and methodologies to support transparency and governance

Required Qualifications

• Bachelor’s degree in Data Analytics, Statistics, Economics, Computer Science, Finance, or a related field (or equivalent experience)
• 3+ years of experience in a data analyst or analytics-focused role
• Strong proficiency in SQL and Excel
• Experience with Tableau and/or Power BI for data visualization and dashboard development
• Working knowledge of Python for data analysis (e.g., pandas, numpy)
• Experience performing data profiling, validation, and basic statistical analysis
• Ability to clearly communicate insights to non-technical stakeholders

Preferred Qualifications

• Commercial real estate (CRE) experience or exposure to real estate, finance, or market data
• Experience working with Salesforce data models and CRM-based datasets
• Familiarity with data lakes and modern data architectures
• Experience supporting broker-facing, client-facing, or revenue-driving teams
• Familiarity with tools such as Ringlead (a plus, not required)
• Experience working with imperfect or incomplete datasets and building trust in data over time

What Success Looks Like

• Data is accurate, well-documented, and trusted by stakeholders
• Dashboards and reports are intuitive, actionable, and widely adopted
• Insights move beyond “what happened” to “what it means” and “what to do next”
• Business teams increasingly rely on data to guide decisions

INCO: “Cushman & Wakefield”