Principle Data Engineer

Required Skills & Experience

Must Haves\n\n\n\t
• Extensive data engineering experience at increasing levels of seniority, with a clear track record of delivering production-grade data platforms and pipelines at scale.\n\t
• 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.\n\t
• Demonstratable experience designing and implementing end-to-end data architectures for complex, enterprise-scale environments.\n\t
• Proven ability to mentor engineers, lead through influence (without direct reports), and raise team-wide standards for technical excellence.\n\t
• 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.

Nice to Have Skills & Experience

Plusses\n\n\t
• Experience embedding across multiple teams, geographies and time zones as a senior technical contributor or technical lead.\n\t
• Familiarity with CI/CD and infrastructure-as-code tooling for data pipelines using Azure DevOps, Databricks Automation Bundles (DABS), GitHub Actions, or equivalent.\n\t
• Good understanding of data governance, metadata management, and cataloguing in enterprise environments\n\t
•

Job Description

Company: Cushman and Wakefield\nPosition: Principle Data Engineer\nLocation: London/US/EU\nSchedule: Monday
- Friday \nOpenings: 1\nSalary (GBP): 180k plus 25% Bonus\nContract: Perm\nExclusive: No\nInterview process/Rounds: 1\nWhy Open: New opening \n \nInsight Global is seeking a highly experienced and influential Principal Data Engineer to serve as one of the most senior technical contributors within the Data Organisation and a recognised expert in modern data engineering practices. This individual will play a critical role in solving the organisation's most complex data engineering challenges, designing scalable data architectures, and driving engineering excellence across global teams.\nThe successful candidate will combine deep hands-on technical expertise with strategic influence, partnering closely with engineering leaders, architects, product teams, and business stakeholders to deliver robust, scalable, and high-performing data solutions. Reporting directly to the Global Head of Data Architecture & Engineering, they will act as a senior technical leader, helping shape the future direction of the organisation's data platforms, architectural standards, and engineering best practices.\n\nThis role requires extensive experience in designing and implementing modern cloud-based data platforms, with a strong focus on Databricks and the Azure ecosystem. The Principal Data Engineer will be expected to move seamlessly across multiple Data Engineering teams, embedding within projects as needed to unblock delivery, accelerate execution, and provide technical leadership on critical initiatives.\nThe individual will be responsible for architecting and implementing scalable data solutions, establishing engineering standards, and ensuring teams adopt best practices in data modelling, data pipelines, platform reliability, observability, and performance optimisation. They will also play a key role in evaluating emerging technologies, advising on future platform capabilities, and driving the adoption of tools and frameworks that support the organisation's evolving data strategy.\n\nAs one of the most senior practitioners within the function, the Principal Data Engineer will mentor engineers at all levels, elevate technical capability across the organisation, and foster a culture of continuous learning and engineering excellence. They will collaborate with leadership teams to define architectural principles, influence technical decision-making, and ensure data engineering practices support both immediate business objectives and long-term strategic goals.\n\nServing as a trusted technical advisor, the Principal Data Engineer will balance hands-on delivery with technical leadership, helping teams navigate complex engineering challenges while establishing the standards, frameworks, and architectural direction that enable the organisation to scale its data capabilities effectively and securely.