Senior Manager - Architect Data Engineering

Job Title

Senior Manager - Architect Data Engineering

Job Description Summary

Cushman & Wakefield is seeking a highly skilled Architect – Data Engineering to play a pivotal role in designing scalable, secure, and high-performing data solutions across the enterprise. Reporting to the Director of Data Engineering & Analytics, this role will focus on architecting the next generation of data platforms, driving the adoption of modern technologies, and ensuring alignment with enterprise goals and governance standards.

As part of Cushman & Wakefield’s broader mission to deliver exceptional value through real estate services, this role serves as a hands-on architect who blends technical depth with strategic insight to shape data engineering, analytics, and AI/ML capabilities in unlocking the power of data to inform decisions, optimize performance, and create competitive advantage for clients and internal stakeholders.

Job Description

Key Responsibilities

• Design and lead end-to-end architecture for modern, cloud-native data engineering, AI/ML and analytics platforms across the full data lifecycle, including ingestion, storage, transformation, and consumption.
• Architect high-performance data solutions using Azure Synapse Analytics, Microsoft Fabric, Azure Databricks, Power BI, Tableau, Python, and other relevant technologies.
• Collaborate with technology leadership and engineering teams to align solutions with enterprise strategy, business goals, and innovation roadmaps.
• Define and enforce standards for data quality, metadata, lineage, and governance in partnership with data governance and MDM teams using tools like Profisee and Azure Purview.
• Provide architectural guidance for AI/ML integrations, including data preparation, feature engineering, and model deployment support.
• Conduct design reviews, architectural assessments, and performance tuning to ensure system reliability, scalability, and maintainability.
• Develop and maintain reusable patterns, frameworks, and coding standards in Python, PySpark, and SQL.
• Collaborate with product managers, engineering leads, analysts, and data scientists to deliver high-impact, cross-functional solutions.
• Drive the evaluation and adoption of emerging technologies in cloud data platforms, streaming analytics, and intelligent automation.
• Mentor data engineers and oversee best practices in solution design, code quality, documentation, and continuous improvement.
• Support DevOps and DataOps initiatives by integrating CI/CD pipelines, Git workflows, and automated testing into engineering workflows.
  
  

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• 10 years of progressive experience in data engineering, data modelling including at least 5 years in an architecture-focused or lead technical role.
• Proven experience architecting enterprise-grade cloud data platforms using Azure, AWS, or Google Cloud.
• Deep expertise in technologies such as Azure Data Factory, Azure Synapse, Databricks, Spark/PySpark, and SQL-based processing.
• Strong grasp of modern data architecture paradigms including data lakehouse, data fabric, microservices, and event-driven design patterns.
• Hands-on experience integrating with data governance and master data management platforms such as Profisee, Azure Purview, or equivalent tools.
• Solid understanding of DevOps and Infrastructure-as-Code practices, including CI/CD pipelines, Docker/Kubernetes, and automated deployment frameworks.
  
  

Preferred Qualifications

• Familiarity with modern data architecture frameworks, including data mesh, data fabric, and data lakehouse.
• Industry experience in commercial or retail real estate, capital projects, or other highly data-driven domains.
• Experience with Database Lifecycle Management (DLM) tools and strong understanding of CI/CD pipelines, branching strategies, and collaborative DevOps practices.
• Proficiency in Python, Scala, or similar programming languages commonly used in large-scale data engineering.
• Understanding of ML/AI model lifecycle architecture, including data preparation, model training, and production deployment best practices.
• Relevant certifications in cloud architecture (e.g., Azure Solutions Architect, AWS Certified Data Analytics) or enterprise architecture (e.g., TOGAF Framework).
  
  

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: $132,600.00 - $156,000.00

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.

In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or email HRServices@cushwake.com. Please refer to the job title and job location when you contact us.

INCO: “Cushman & Wakefield”