Data Analytics Engineer

Overview

As a Data Analytics Engineer on Cushman & Wakefield's Portfolio Advisory Group, 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.

What you'll do

• 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.
• 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.
• 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.
• 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.
• 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.

What you'll need

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

Nice to have

• 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.

Details

• Location: Remote, United States (flexible).
• Compensation: $106,250.00 - $125,000.00.