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About the Role

The Principal Data Engineer 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. 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

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.
Write, review, and refactor production code that exemplifies the team’s standards for performance, reliability, security, observability, and cost efficiency.
Help define and continuously evolve the engineering and architectural principles, patterns, and reference implementations used across the Data Organization.
Maintain near-expert depth in Databricks and Azure data services and proactively build expertise in adjacent and emerging technologies.
Design end-to-end data architectures – covering ingestion, storage, transformation, serving, and governance – using Lakehouse patterns on Databricks and the Azure data ecosystem.
Implement and validate critical components of the architectures you design, ensuring they are demonstrably production ready.
Partner with the Architecture function to ensure designs align with enterprise standards for security, governance, scalability, and total cost of ownership.
Mentor data engineers across all levels through code reviews, pairing, design reviews, and direct coaching.
Lead internal tech talks and written deep dives on patterns, pitfalls, and platform capabilities.
Embed 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 identify technical risks, design flaws, and execution gaps, and drive issues to resolution with clear, well-reasoned recommendations.
Serve as the go-to technical voice for complex data problems and platform capabilities.
Translate business needs into clear technical strategies and translate technical trade-offs into language that supports informed decisions.
Collaborate with peers in Architecture, Platform, AI, Analytics, Security, and Governance to ensure data engineering work integrates cleanly into the broader data and technology landscape.

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

Skills

Databricks
Azure data ecosystem
Spark
Lakeflow
Spark Declarative Pipelines (DLT)
Delta Lake
Lakebase/Postgres
Unity Catalog
Lakehouse patterns
Medallion architecture
Data mesh
DataOps practices
CI/CD
Infrastructure-as-code
Azure DevOps
Databricks Automation Bundles (DABS)
GitHub Actions
Data governance
Metadata management
Data cataloguing

Location

Hybrid/Remote depending on location
US/EMEA time zone

Work Type

Hybrid
Remote

Experience Level

Principal
Senior

About the Company

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.

Equal Opportunity

Cushman & Wakefield is an equal opportunity / affirmative action employer.
All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic.
Cushman & Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace.
If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor’s attention once they have made contact.