Data Engineering Manager — AI‑Driven Platforms

Ernst & Young Oman; Alpharetta (GA); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Generous vacation policy

Job summary

EY in the United States seeks a Data Engineering Manager to design and build AI and analytics solutions that deliver business value. You will lead cross-functional teams across data engineering, analytics, and software, translating requirements into scalable data architectures.

The role emphasizes collaboration with clients, managing resources and budgets, and delivering complex technical initiatives across the data lifecycle. Travel may be 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, data pipelines, streaming architectures, and big data ecosystems.

Responsibilities

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

Skills

Leading teams

Data engineering

Cross-functional collaboration

Communication

Ambiguity management

Client relationships

Problem solving

ML concepts

Education

Bachelor’s degree in Data Science, Machine Learning, CS, Statistics, Math, Engineering, Analytics

Tools

Python

R

SQL

Cloud Computing

Job description

EY in the United States seeks a Data Engineering Manager to design and build AI and analytics solutions that deliver business value. You will lead cross-functional teams across data engineering, analytics, and software, translating requirements into scalable data architectures.

The role emphasizes collaboration with clients, managing resources and budgets, and delivering complex technical initiatives across the data lifecycle. Travel may be required.