Director, Data Engineering Delivery

Cushman & Wakefield

2d•$140,250 - $165,000•Hybrid

About The Position

Reporting to the Global Head of Data Architecture & Engineering, the Director of Data Engineering Delivery will be a member of the Global Data Leadership team and will help shape data engineering strategy, standards, and execution across the organization. The role requires fluency with Databricks and the Azure ecosystem today, and the adaptability to evaluate and adopt additional data technologies as our platform evolves. The Director of Data Engineering Delivery will be equally comfortable managing the deliverables and pipeline of work for a team of data engineers as they are building data platforms and developing the engineers who build on them. This is a hybrid technical and people leadership role: the successful candidate will lead, mentor, and grow a team of 5–8 data engineers and analysts whilst also contributing hands-on to data engineering deliverables on Databricks and Azure.

Requirements

Fluency with Databricks and the Azure ecosystem
Ability to evaluate and adopt additional data technologies
Experience managing the deliverables and pipeline of work for a team of data engineers
Experience building data platforms
Experience developing engineers who build on data platforms
Experience leading, mentoring, and growing a team of data engineers and analysts
Hands-on contribution to data engineering deliverables on Databricks and Azure

Responsibilities

Lead the design, build, and continuous improvement of scalable data pipelines, Lakehouse architectures, and data products on Databricks and Azure, ensuring our engineering and architectural standards for performance, reliability, and cost are consistently delivered.
Remain an active practitioner by contributing to high-impact pipelines, code reviews, architecture reviews, and complex troubleshooting.
Champion data quality, observability, security, and governance practices, embedding them into the team’s engineering lifecycle and platform standards.
Directly manage a team of 5–8 data engineers, owning hiring, onboarding, performance management, compensation recommendations, and retention.
Provide regular coaching, feedback, and career development planning for each team member, with clear growth paths for both individual contributor and leadership tracks.
Foster an inclusive, high-trust team culture grounded in psychological safety, technical curiosity, accountability, and continuous learning.
Plan, prioritize, and orchestrate the team’s portfolio of data engineering work, ensuring on-time, on-quality delivery aligned with global data and business priorities.
Establish and refine agile delivery practices (intake, estimation, sprint planning, retrospectives) that balance discovery work, platform investment, and run-the-business commitments.
Proactively identify, communicate, and resolve risks, blockers, and cross-team dependencies, escalating clearly and constructively when needed.
Own production health for the team’s data products, including SLAs, on-call posture, incident response, and post-incident learning.
Build trusted relationships with business and technology stakeholders, translating their objectives into clearly scoped, prioritized data engineering outcomes.
Partner closely with peers across the Global Data Leadership team - architecture, data engineering, AI, governance, and product - to deliver cohesive, end-to-end data solutions.
Communicate technical concepts, trade-offs, roadmaps, and progress effectively to audiences ranging from engineers to senior executives.