Data Engineering Manager: AI & Analytics Leader

Ernst & Young Oman; Salt Lake City (UT); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY is seeking a Data Engineering Manager to design and deliver scalable AI and analytics solutions for top clients. You will lead data architecture, modeling, and production handoffs while collaborating with cross-functional teams across the globe.

The role demands strong communication, client management, and technical hands-on expertise in Python, R, and SQL, with a focus on quality, bias checks, and secure data practices. Travel may be required.

Qualifications

• Bachelor’s degree required in Data Science, Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Applied Math, 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, data pipelines, streaming architectures, and big data ecosystems.
• Cloud Computing Architecture
• Data Architecture Design and Modelling
• Data Integration
• Data Security
• Ontology Design
• Software Engineering
• Data Quality
• Database Management
• Semantic Layer
• Building and Managing Relationships
• Client Trust and Value
• Communicating With Impact
• Hybrid Collaboration
• Commercial Acumen
• Leading Teams
• Managing Change

Responsibilities

• Leading workstream delivery and ensuring quality in all processes.
• Engaging with clients on a daily basis, actively participating in working sessions, and identifying opportunities for additional services.
• Implementing resource plans and budgets while managing engagement economics.

Skills

Python

R

SQL

Education

Bachelor’s degree in Data Science/Computer Science/Engineering

Job description

EY is seeking a Data Engineering Manager to design and deliver scalable AI and analytics solutions for top clients. You will lead data architecture, modeling, and production handoffs while collaborating with cross-functional teams across the globe.

The role demands strong communication, client management, and technical hands-on expertise in Python, R, and SQL, with a focus on quality, bias checks, and secure data practices. Travel may be required.