Director, Data Engineering Delivery

🕒 September 16

🇺🇸 United States – Remote

💵 $140.3k - $165k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Cushman & Wakefield

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1917

💼 Consulting

🏥 Healthcare

🏗️ Construction

Consulting • Healthcare • Construction

Cushman & Wakefield is a global leader in commercial real estate services, providing a wide range of services including agency leasing, asset services, capital markets, global occupier services, project and development services, tenant representation, and valuation and advisory for various industries such as logistics and industrial, multifamily, retail, life sciences, data centers, and healthcare. The company is committed to driving forward for clients, colleagues, and communities with a focus on diversity, equity, and inclusion, as well as environmental, social, and governance principles. Operating in over 60 countries with 52,000 professionals, Cushman & Wakefield consistently delivers insights and research, such as market reports and sustainability efforts.

📋 Description

• Shape data engineering strategy, standards, and execution across the organization • Lead the design, build, and continuous improvement of scalable data pipelines, Lakehouse architectures, and data products on Databricks and Azure • Contribute hands-on to high-impact pipelines, code reviews, architecture reviews, and complex troubleshooting • Champion data quality, observability, security, and governance practices • Directly manage a team of 5–8 data engineers and analysts • Own hiring, onboarding, performance management, compensation recommendations, and retention • Provide coaching, feedback, and career development planning • Foster an inclusive, high-trust team culture • Plan, prioritize, and orchestrate the team’s data engineering portfolio • Establish and refine agile delivery practices • Identify, communicate, and resolve risks, blockers, and cross-team dependencies • Own production health, including SLAs, on-call posture, incident response, and post-incident learning • Build relationships with business and technology stakeholders and translate objectives into prioritized data engineering outcomes • Collaborate with the Global Data Leadership team across architecture, data engineering, AI, governance, and product • Communicate technical concepts, trade-offs, roadmaps, and progress to engineers and senior executives

🎯 Requirements

• Fluency with Databricks and the Azure ecosystem • Adaptability to evaluate and adopt additional data technologies as the platform evolves • Experience managing deliverables and work pipelines for a team of data engineers • Experience building data platforms and developing data engineers • Ability to lead, mentor, and grow a team of 5–8 data engineers and analysts • Hands-on experience contributing to data engineering deliverables on Databricks and Azure • Experience with scalable data pipelines, Lakehouse architectures, and data products • Knowledge of engineering and architectural standards for performance, reliability, and cost • Experience with code reviews, architecture reviews, and complex troubleshooting • Knowledge of data quality, observability, security, and governance practices • Experience with hiring, onboarding, performance management, compensation recommendations, and retention • Experience providing coaching, feedback, and career development planning • Experience planning and orchestrating a portfolio of data engineering work • Knowledge of agile delivery practices, including intake, estimation, sprint planning, and retrospectives • Experience with risk, blocker, dependency, SLA, on-call, incident response, and post-incident management • Ability to build relationships with business and technology stakeholders • Ability to communicate technical concepts, trade-offs, roadmaps, and progress to engineers and senior executives

🏖️ Benefits

• Health insurance • Vision insurance • Dental insurance • Flexible spending accounts • Health savings accounts • Retirement savings plans • Life insurance • Disability insurance programs • Paid and unpaid time away from work • Competitive pay