Data Analytics Engineer

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., Data Engineering & Pipeline Development

• Design, develop, maintain, and troubleshoot ETL/ELT pipelines that ingest, transform, validate, and deliver data from multiple sources into centralized data platforms.
• Build and optimize data processing workflows using Databricks or Microsoft Fabric to support scalable analytics and reporting requirements.
• Automate and improve recurring data processes to strengthen pipeline performance, reliability, and operational efficiency.

Data Modeling & Integration

• Develop and maintain structured data models, including dimensional models where appropriate, that support business intelligence, dashboards, reporting, and analytical use cases.
• Integrate and organize data from multiple source systems into accessible, consistent datasets designed for downstream consumption.
• Prepare and transform data to enable visualization, reporting, business analysis, and stakeholder decision-making.

Data Quality, Governance & Reliability

Implement data validation, quality controls, governance practices, and documentation that improve the accuracy and reliability of analytical data.

• Identify and resolve data issues, inconsistencies, and pipeline failures that could affect reporting quality or stakeholder confidence.
• Document data structures, transformations, business rules, and technical processes to support transparency, maintainability, and consistent use.

Business Intelligence & Data Accessibility

• Develop datasets and data structures that enable dashboards, visualization, reporting, and other stakeholder-facing analytical solutions.
• Support dashboard and visualization development using Power BI or comparable business intelligence platforms.
• Improve how business users and analytics teams access and use trusted data for recurring reporting and decision support.

Stakeholder Partnership & Continuous Improvement

• Partner with client stakeholders, analytics teams, business leaders, and technical partners to gather requirements and translate business needs into technical solutions.
• Communicate technical concepts, data limitations, dependencies, and delivery progress clearly to technical and nontechnical stakeholders.
• Identify and implement opportunities to automate data workflows, reduce manual processes, improve maintainability, and support geospatial or location-intelligence requirements where applicable.

Must-Have Requirements

• 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.

Preferred Experience

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

Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.

The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications.

The company will not pay less than minimum wage for this role.

The compensation for the position is: $ 106,250.00 - $125,000.00

Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.