Data Engineering Manager: AI & Analytics Lead

Ernst & Young Oman; Des Moines (IA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical/dental coverage

Pension/401(k)

Job summary

EY is seeking a Data Engineering Manager to design and deliver AI-driven analytics solutions. You will collaborate across data teams and clients to ensure requirements align with business goals, building scalable architectures and production-ready pipelines.

You will manage cross-functional projects, travel as needed, and mentor teams in a dynamic hybrid environment. A strong foundation in data engineering and cloud architectures is required.

Qualifications

• Bachelor’s degree required in Data Science, ML, CS, Statistics, Mathematics, Engineering, Analytics, or related preferred.
• Typically, no less than 4-6 years relevant experience.
• Hands-on experience developing scalable data solutions using Python, R, and SQL, with expertise in data engineering, pipelines, streaming, and big data ecosystems.

Responsibilities

• Designing and building AI and analytics solutions that deliver significant business value.
• Collaborating with data and analytics professionals, management, and stakeholders to align technical requirements with business needs.
• Creating scalable data architectures and modeling solutions across the data asset lifecycle.

Skills

Stakeholder management

Cross-functional collaboration

Project delivery

Communication

Analytical thinking

Cloud and distributed systems

AI/GenAI tooling

Problem solving

Leadership

Change management

Education

Bachelor’s degree in Data Science/CS/Engineering

Tools

Python

SQL

R

Cloud (AWS/Azure/GCP)

Job description

EY is seeking a Data Engineering Manager to design and deliver AI-driven analytics solutions. You will collaborate across data teams and clients to ensure requirements align with business goals, building scalable architectures and production-ready pipelines.

You will manage cross-functional projects, travel as needed, and mentor teams in a dynamic hybrid environment. A strong foundation in data engineering and cloud architectures is required.