Principal Engineer

Cushman & WakefieldAmsterdamHybridFull-time1 week ago

Cushman & Wakefield seeks a Principal Data Engineer to serve as a senior technical leader within the TDS Technology and Data Solutions team. The role involves designing and implementing scalable data architectures on Databricks and Azure, mentoring engineers, and driving engineering excellence across the Data Organization.

What you'll do

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 on our roadmap.
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, with a particular focus on accelerating mid-level engineers toward senior contribution.
Lead internal tech talks and written deep dives on patterns, pitfalls, and platform capabilities to multiply the team’s expertise.
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.

What you need

Must-have

DatabricksApache SparkLakeflowSpark Declarative Pipelines (DLT)Delta LakeLakebasePostgreSQLUnity Catalog

Nice-to-have

CI/CDInfrastructure-as-CodeAzure DevOpsDatabricks Automation Bundles (DABS)GitHub ActionsData GovernanceMetadata ManagementData Cataloguing

Soft skills

MentorshipLeadershipCommunicationInfluenceCollaborationProblem SolvingTechnical Advisory

Data EngineeringDatabricksAzureReal EstatePrincipal EngineerHybridFull-timeData ArchitectureMentorshipLakehouse

/What you'll do

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Must-have

Nice-to-have

Soft skills

What you'll do

What you need