[Hiring] Data Analytics Engineer @Cushman & Wakefield

Role Description

As the Data & Analytics Engineer, you will build and maintain scalable data pipelines, data models, and organized datasets that enable reliable analytics, reporting, and business decision-making across strategic client accounts. You will translate business and data requirements into durable technical solutions, with hands-on ownership of data ingestion, transformation, integration, quality, and preparation for downstream business intelligence and visualization.

As a member of Cushman & Wakefield’s Portfolio Advisory Group, the Data & Analytics Engineer will be dedicated to one or more of Cushman & Wakefield’s most dynamic client accounts. In this role, you will collaborate closely with peers and the account team to support a client's strategic real estate vision. The Data & Analytics Engineer will embody our team philosophy “Client First, Insight Always, Execution Excellence”, ensuring every deliverable reflects the team’s commitment to innovation, collaboration, and measurable impact.

This role will primarily:

• Build and maintain scalable ETL/ELT pipelines and data structures that integrate information from multiple sources and make trusted data accessible for analytics and reporting.
• Transform, model, validate, and organize data so stakeholders can rely on consistent datasets for dashboards, visualization, reporting, and decision support.
• Translate client and business requirements into practical data engineering solutions using Databricks or Microsoft Fabric, SQL, and related technologies.
• Improve data accessibility, reliability, and delivery efficiency through automation, data quality controls, documentation, and technical process improvement.

Success in this role looks like:

• Data pipelines consistently deliver reliable, accurate, and accessible datasets for downstream analytics and stakeholder-facing solutions.
• Data models and transformations support scalable reporting and reduce dependence on manual data preparation.
• Data quality controls and documentation improve confidence, consistency, and usability across analytics outputs.
• Business requirements are translated into maintainable technical solutions that stakeholders and analytics teams can effectively use.

Qualifications

• Approximately 3–4+ years of relevant experience in data engineering, analytics engineering, business intelligence, or a closely related field.
• Hands-on experience with Databricks or Microsoft Fabric, including practical experience developing data solutions rather than solely consuming platform outputs.
• Demonstrated experience building, maintaining, and troubleshooting ETL/ELT pipelines.
• Strong working knowledge of SQL, data transformation, data integration, and data modeling.
• Experience preparing structured datasets for business intelligence, dashboards, reporting, visualization, or stakeholder consumption.
• Understanding of data quality, validation, governance, and data-management practices.
• Demonstrated ability to translate business requirements into technical deliverables and collaborate effectively with business, client, and technical stakeholders.

Requirements

• Experience working with both Databricks and Microsoft Fabric.
• Experience with Lakehouse architecture, Delta Lake, Unity Catalog, or comparable modern data-platform technologies.
• Experience using Python or another programming language for data engineering or automation.
• Experience developing or supporting solutions in Power BI, Tableau, or comparable visualization platforms.
• Experience with dimensional modeling, data warehousing, enterprise reporting, or enterprise data-management frameworks.
• Experience with Esri/ArcGIS, geospatial analytics, mapping, or location intelligence.
• Experience supporting enterprise clients, consulting engagements, client-facing analytics initiatives, or AI-enabled analytics technologies.

Technology & Tools

• Databricks and/or Microsoft Fabric
• SQL and ETL/ELT development technologies
• Data modeling, integration, and modern data-platform technologies
• Python
• Power BI or comparable business intelligence and visualization tools
• Delta Lake, Unity Catalog, or related Lakehouse technologies
• Esri/ArcGIS and geospatial analytics tools, where applicable
• AI-enabled analytics and automation solutions

Capabilities

• Technical problem-solving and structured analytical thinking.
• Ability to translate business requirements into scalable technical solutions.
• Strong attention to data accuracy, reliability, maintainability, and usability.
• Clear communication of technical concepts to business and client stakeholders.
• Organization and prioritization across concurrent technical requirements and projects.
• Cross-functional collaboration across business, analytics, and technical teams.
• Continuous improvement mindset focused on automation, scalability, data accessibility, and measurable business impact.

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Data Analytics, or a related field preferred; equivalent relevant professional experience may be considered.

Benefits

• Health, vision, and dental insurance
• Flexible spending accounts
• Health savings accounts
• Retirement savings plans
• Life and disability insurance programs
• Paid and unpaid time away from work
• Competitive pay based on eligibility factors