Senior Manager, Data Engineering

Cushman & Wakefield

. Lead the design, build, and continuous improvement of scalable data pipelines, Lakehouse architectures, and data products on Databricks and Azure .

Posted 10/14/2026full-timeRemote • United StatesSenior💰 $140,250 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering teams and managing scalable data pipelines using Databricks and Azure. Proficient in establishing data quality, security, and governance practices while fostering a collaborative team culture.

Highest-signal resume keywords

Data Engineering ExperienceDatabricks ProficiencyAzure Data Ecosystem KnowledgeTeam Management SkillsAgile Delivery Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentLakehouse ArchitectureSpark Declarative PipelinesDelta LakeDataOps PracticesMetadata-Driven Pipeline FrameworksCI/CD ToolingInfrastructure-As-CodeProduction-Grade Data PlatformsPerformance Management

Soft Skills

Excellent CommunicationStakeholder ManagementPrioritization SkillsClient-Service MindsetTeam Culture Development

Tools & Technologies

DatabricksAzure DevOpsGitHub ActionsDatabricks Automation BundlesLakebase/Postgres

Industry Keywords

Data QualityData GovernanceAgile MethodologiesCross-Team CollaborationGlobal Team Management

Tech Stack

Tools & technologies

AzurePostgresSparkUnity

About the role

Key responsibilities & impact

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, including 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, including intake, estimation, sprint planning, and retrospectives
Identify, communicate, and resolve risks, blockers, and cross-team dependencies
Own production health for the team’s data products, 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
Partner with architecture, data engineering, AI, governance, and product teams to deliver end-to-end data solutions
Communicate technical concepts, trade-offs, roadmaps, and progress to engineers and senior executives
Help shape data engineering strategy, standards, and execution across the organization

Requirements

What you’ll need

Significant data engineering experience
Hands-on experience with Databricks, including Spark, Lakeflow, Spark Declarative Pipelines (DLT), Delta Lake, Lakebase/Postgres, and Unity Catalog
Experience with the Azure data ecosystem
Demonstrable experience formally managing data engineers, including hiring, performance management, and career development
Track record of delivering production-grade data platforms and pipelines at scale
Strong attention to reliability, security, and cost
Ability to lead complex technical work through influence, not authority
Excellent communication, stakeholder management, and prioritization skills in a global, matrixed environment
Client-service mindset
Familiarity with modern data architecture patterns, including Lakehouse, Unity Catalog, medallion, and data mesh
Familiarity with DataOps practices
Familiarity with metadata-driven and configuration-driven pipeline frameworks
Experience leading teams through technology transitions and adopting new data tooling
Familiarity with CI/CD and infrastructure-as-code tooling, including Azure DevOps, Databricks Automation Bundles (DABS), GitHub Actions, or equivalent
Experience leading cross-team initiatives across multiple geographies and time zones
Ability to work in the US/EMEA time zone

Benefits

Comp & perks

Health insurance
Vision insurance
Dental insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life insurance
Disability insurance
Paid time away from work
Unpaid time away from work
Competitive pay
Inclusive culture
Career development planning and coaching