Manager - Data Engineering & Analytics

Cushman & Wakefield is seeking a highly skilled Manager Data Engineering & Analytics to lead the design, implementation, and governance of scalable, secure, and high-performing data solutions across the enterprise. Reporting to the Director of Data Engineering & Analytics, this hands-on leadership role focuses on modernizing the data platform, guiding the adoption of emerging technologies, and ensuring alignment with organizational goals and compliance standards.

As part of Cushman & Wakefields mission to deliver exceptional value through real estate services, this role plays a key part in enabling enterprise-wide data strategy, analytics, and AI/ML capabilitiesunlocking insights that drive performance, optimize operations, and enhance client value.

Job Description

About the Role:

• Lead the design and execution of modern, cloud-native data engineering, AI/ML and analytics platforms across the full data lifecycle, including ingestion, storage, transformation, and consumption.
• Develop scalable, high-performance data solutions using Azure Synapse Analytics, Microsoft Fabric, Azure Databricks, Power BI, Tableau, Python, and other relevant technologies.
• Manage and mentor a team of data engineers, fostering a culture of engineering excellence, knowledge sharing, and continuous improvement.
• Collaborate with engineering, product, and business leadership to ensure alignment of data solutions with enterprise goals, technology roadmaps, and innovation priorities.
• Define and enforce standards for data quality, lineage, and metadata in coordination with data governance and MDM teams using tools such as Profisee and Azure Purview.
• Oversee architectural reviews, performance tuning, and system reliability initiatives to support scalable enterprise data platforms.
• Establish and maintain reusable development patterns and coding standards in Python, PySpark, and SQL.
• Guide the integration of AI/ML solutions through architectural planning, data readiness, and scalable deployment pipelines.
• Evaluate and implement emerging technologies in cloud data platforms, streaming analytics, and intelligent automation.
• Champion DevOps and DataOps best practices, including CI/CD pipeline development, Git-based workflows, and automated testing.
• Ensure comprehensive technical documentation and foster collaboration across cross-functional data and analytics teams.

About You:

• Bachelors or Masters degree in Computer Science, Information Systems, Data Engineering, or a related field.
• 8+ years of progressive experience in data engineering and analytics, including 5+ years in technical leadership, team management and/or architecture-focused roles.
• Proven experience designing and deploying enterprise-grade cloud data platforms using Azure, AWS, or Google Cloud.
• Deep hands-on expertise with Azure Synapse Analytics, Azure Data Factory, Databricks, Spark/PySpark, and SQL-based data processing.
• Strong knowledge of modern data architecture patterns such as data lakehouse, data fabric, microservices, and event-driven pipelines.
• Experience integrating data governance and MDM solutions, particularly with Profisee, Azure Purview, or similar platforms.
• Working knowledge of DevOps practices and Infrastructure-as-Code principles including CI/CD pipelines, Docker/Kubernetes, and automation frameworks.
• Familiarity with emerging data architecture models such as data mesh and unified data platforms.
• Industry experience in commercial real estate, capital projects, or other data-rich operational environments.
• Experience with Database Lifecycle Management (DLM) tools and collaborative Git-based development practices.
• Proficiency in modern programming languages such as Python or Scala, used in scalable data engineering.
• Understanding of the ML/AI model lifecycle including data preparation, model training, and production deployment.
• Relevant certifications such as Azure Solutions Architect, AWS Data Analytics, TOGAF, or similar enterprise architecture credentials.