Software Engineer
In 2023, the firm reported revenue of $9.5 billion across its core services of property, facilities and project management, leasing, capital markets, and valuation and other services.
Job Title
Job Description Summary
Job Description
Job Title: Principal Data Engineer
Position: Principal Data Engineer
Department: TDS Technology and Data Solutions
Reports To: Global Head of Data Architecture & Engineering
Location: Hybrid/Remote depending on location, Working time zone: US/EMEA
Cushman & Wakefield (NYSE: CWK) is a leading global commercial real estate services firm for property owners and occupiers with approximately 52,000 employees in nearly 400 offices and 60 countries. In 2023, the firm reported revenue of $9.5 billion across its core services of property, facilities and project management, leasing, capital markets, and valuation and other services. It also receives numerous industry and business accolades for its award-winning culture and commitment to Diversity, Equity and Inclusion (DEI), sustainability and more. For additional information, visit www.cushmanwakefield.com.
Career Level: P7
Role Summary:
We are seeking a Principal Data Engineer to serve as one of the most senior data engineers on our team and a near-expert practitioner in the domain. This role combines deep technical execution with broad influence: tackling the most complex data engineering problems, designing and implementing data architectures, and raising the bar for engineering excellence across the Data Organization.
Reporting to the Global Head of Data Architecture & Engineering, the Principal Data Engineer is expected to move fluidly across Data Engineering teams - embedding in projects for days or months at a time to unblock, accelerate, and uplift delivery. They will mentor engineers at every level, push standards for technical excellence, and help establish the engineering and architectural principles that guide our work. The primary platform is Databricks and the Azure cloud ecosystem, with the expectation of evaluating and adopting additional data technologies as the platform evolves.
Key Responsibilities:
Technical Data Engineering Execution
< >Engineering delivery: Take on the most technically demanding data engineering work – high-scale pipelines, performance-critical workloads, workload optimization, and platform-level capabilities on Databricks and Azure – where deep expertise is essential to success.Engineering excellence: Write, review, and refactor production code that exemplifies the team’s standards for performance, reliability, security, observability, and cost efficiency.Standards and principles: Help define and continuously evolve the engineering and architectural principles, patterns, and reference implementations used across the Data Organization.Continuous learning: Maintain near-expert depth in Databricks and Azure data services and proactively build expertise in adjacent and emerging technologies on our roadmap. Data Architecture
Posted July 31, 2026