Principal Engineer

About the role

The Principal Data Engineer at Cushman & Wakefield is a senior, high-impact technical leader responsible for solving complex data engineering challenges and shaping enterprise-wide data architecture within the TDS Technology and Data Solutions team. Reporting to the Global Head of Data Architecture & Engineering, this role combines deep hands-on expertise with strategic influence—designing and implementing scalable data solutions on Databricks and the Azure ecosystem, establishing engineering standards, and driving architectural best practices.

Responsibilities

• Taking 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.
• Writing, reviewing, and refactoring production code that exemplifies the team’s standards for performance, reliability, security, observability, and cost efficiency.
• Helping define and continuously evolve the engineering and architectural principles, patterns, and reference implementations used across the Data Organization.
• Mentoring engineers at every level, pushing standards for technical excellence, and helping establish the engineering and architectural principles that guide our work.
• Embedding into Data Engineering teams for engagements ranging from days to months to lead, accelerate, or de-risk critical projects, transferring expertise back to the host team upon exit.
• Proactively identifying technical risks, design flaws, and execution gaps, and driving issues to resolution with clear, well-reasoned recommendations.
• Serving as the go-to technical voice for complex data problems and platform capabilities, translating business needs into clear technical strategies and translating technical trade-offs into language that supports informed decisions.

Requirements

• Extensive data engineering experience at increasing levels of seniority, with a clear track record of delivering production-grade data platforms and pipelines at scale.
• Near-expert hands-on proficiency with Databricks (Spark, Lakeflow, Spark Declarative Pipelines (DLT), Delta Lake, Lakebase/Postgres, Unity Catalog, etc.) and the Azure data ecosystem.
• Demonstratable experience designing and implementing end-to-end data architectures for complex, enterprise-scale environments.
• Prominent ability to mentor engineers, lead through influence (without direct reports), and raise team-wide standards for technical excellence.
• Familiarity with modern data architecture patterns (Lakehouse, medallion, data mesh), DataOps practices, and metadata-driven and configuration-driven pipeline frameworks and a strong instinct for reusable, scalable engineering patterns.

Qualifications

• Good understanding of data governance, metadata management, and cataloguing in enterprise environments.

Skills

• Experience embedding across multiple teams, geographies and time zones as a senior technical contributor or technical lead.
• Familiarity with CI/CD and infrastructure-as-code tooling for data pipelines using Azure DevOps, Databricks Automation Bundles (DABS), GitHub Actions, or equivalent.

Benefits

Cushman & Wakefield 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 provides 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.

Pay

$ 157,250.00 - $185,000.00

Schedule

Hybrid/Remote depending on location, Working time zone: US/EMEA