Cloud & Data Engineering Manager - Lead Data Platforms

EY; Sacramento (CA); Remote; USD 126,000 - 251,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable, reliable production solutions across Azure, AWS, and GCP. You will own workstreams, manage budgets, and engage with clients while leading technical teams to deliver high-availability cloud Data platforms.

You’ll design pipelines, govern data assets, and apply GenAI capabilities where relevant, while promoting Agile practices and strong operational governance.

Qualifications

• Bachelor's degree required; four-year degree.
• 4–6 years of relevant experience or more.
• Proven experience with Azure services and cloud platforms.
• Experience designing and managing container orchestration in Kubernetes.

Responsibilities

• Lead one or more technical workstreams with delivery quality.
• Translate client requirements into architecture, pipelines, and production platforms.
• Maintain daily client engagement and identify adjacent service opportunities.
• Manage resource plans, budgets and engagement economics.
• Own problems from data sources to production handoff and monitoring.
• Embed governance, observability, and operational support across teams.

Skills

Cloud data engineering

Leadership & people management

Agile methodologies

Client engagement

Strong communication

Problem-solving

Education

Bachelor's degree

Tools

Azure Kubernetes Service (AKS)

Kubernetes

Terraform

GitHub Actions

Azure DevOps

Azure Functions

Azure Container Apps

CI/CD

Job description

EY is seeking a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable, reliable production solutions across Azure, AWS, and GCP. You will own workstreams, manage budgets, and engage with clients while leading technical teams to deliver high-availability cloud Data platforms.

You’ll design pipelines, govern data assets, and apply GenAI capabilities where relevant, while promoting Agile practices and strong operational governance.