Remote Cloud & Data Engineering Manager - AI Lead

EY; Stamford (CT); On-site; USD 126,000 - 230,000; 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. You will own workstreams, engage clients, manage budgets, and guide cross-functional teams across data engineering, software engineering, AI/ML, and governance.

You will design cloud platforms, build scalable pipelines with Python/SQL on Azure (with AWS/GCP as secondary), and drive production readiness, observability, and quality across the platform.

Qualifications

• A 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 Azure Functions, Azure Container Apps, Azure SQL Database, Azure Blob Storage, AKS, Azure Monitor, 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 Kubernetes Service (AKS)

Terraform

GitHub Actions

Azure DevOps

Kubernetes

SRE fundamentals

Data engineering

GenAI / LLM capabilities

Agile delivery

Cloud platforms (Azure, AWS, GCP)

Education

Bachelor's degree

Tools

Azure Functions

Azure Container Apps

Azure SQL Database

Azure Blob Storage

AKS

Azure Monitor / Prometheus

Kubernetes

Terraform

GitHub Actions

Azure DevOps

Job description

EY is seeking a Data and Cloud Engineering Manager to turn data and AI capabilities into scalable, reliable production solutions. You will own workstreams, engage clients, manage budgets, and guide cross-functional teams across data engineering, software engineering, AI/ML, and governance.

You will design cloud platforms, build scalable pipelines with Python/SQL on Azure (with AWS/GCP as secondary), and drive production readiness, observability, and quality across the platform.