Lead Cloud & Data Engineering Manager

EY; Portland (OR); Remote; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off options

Job summary

EY in the United States seeks a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable, reliable production solutions—from assessment through ingestion, transformation, governance and production handoff. You will own workstreams, budgets and client interactions.

Lead cross‑functional teams across data engineering, software engineering, AI/ML and cloud platforms (Azure as primary, AWS/GCP as needed).

Qualifications

• Bachelor's degree required (4-year degree).
• Typically, no less than 4 - 6 years of relevant experience.
• Proven record operating High Availability services on Azure (4+ years).
• Expert understanding of core Azure services such as but not limited to: Azure Functions, Azure Container Apps (or Azure App Service), Azure SQL Database, Azure Blob Storage, Azure Kubernetes Service (AKS), Azure Monitor (Log Analytics & Application Insights), and Azure Managed Prometheus.
• Experience designing, deploying and managing container orchestration platforms using Kubernetes
• Experience implementing SRE standards for Resiliency and Scalability of microservice architectures in Kubernetes
• Experience with infrastructure automation using Terraform
• Experience implementing SLIs, SLOs and Error Budgets as part of development/delivery practices
• Experience monitoring container based microservices & Cloud Platform services
• Use of CI/CD tools - preferably GitHub Actions, Azure DevOps
• Knowing agile methodology and being able to work by its principles
• Strong analytical and problem-solving skills
• Self-starter and strong, quick problem-solving skills

Responsibilities

• Lead one or more technical workstreams and assure delivery quality.
• Translate business and client requirements into architecture, pipelines, models, semantic layers or production platforms.
• Maintain daily client engagement, participate in working sessions and identify adjacent service opportunities.
• Manage resource plans, budgets and engagement economics.
• Own problems from raw source through data pipeline, model/analysis and production handoff.
• Automate, optimize and drive efficiency in processes, tools and communication across cross-functional teams (e.g. spanning data engineering, software engineering, AI/ML, architecture, cloud and governance).
• Remain hands-on: tested, version-controlled, observable code rather than one-off analytical notebooks
• Work closely with development teams and participate in planning sessions to achieve high level of availability, reliability and performance of their service and platform requirements
• Design, provision, and run the underlying cloud and container platform that application teams rely on in production
• Build scalable pipelines and streaming architectures using Python/SQL and cloud platforms (Azure predominantly, AWS and GCP also key platforms)
• Understand and apply data architecture, modelling, integration, quality, security, ontologies and semantic layers
• Understand and apply quality assurance and testing practices.
• Understand and apply cloud and distributed-system architecture and the path to production using Kubernetes, GPU infrastructure, multi-tenancy, infrastructure-as-code, GitOps, resilience and hybrid/multi-environment portability
• Incorporate GenAI/LLM capabilities where relevant
• Demonstrate proficiency in Agile delivery and development methodologies.
• Embed governance, observability, controls and operational support—not stop at model development or analysis

Skills

Azure cloud engineering

Kubernetes

Data pipelines

Python/SQL

Agile methodologies

Client engagement

Problem solving

Communication

Education

Bachelor's degree

Tools

Azure Functions

Azure Container Apps

Azure SQL Database

Azure Kubernetes Service (AKS)

Azure Monitor (Log Analytics & Application Insights)

Terraform

GitHub Actions

Azure DevOps

Job description

EY in the United States seeks a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable, reliable production solutions—from assessment through ingestion, transformation, governance and production handoff. You will own workstreams, budgets and client interactions.

Lead cross‑functional teams across data engineering, software engineering, AI/ML and cloud platforms (Azure as primary, AWS/GCP as needed).