Data Engineering Manager — AI, Cloud & Analytics

Ernst & Young Oman; Southfield (MI); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

401(k) plan

Job summary

EY in the United States seeks a Data Engineering Manager to lead AI‑driven data platform initiatives. You will design scalable data architectures and production pipelines, collaborating with data scientists, engineers, and clients to align technical outcomes with business needs.

You will oversee cross‑functional teams, manage budgets, and ensure quality while delivering trusted data insights and value for stakeholders.

Qualifications

• Bachelor’s degree required in data science, CS, statistics, or a related field.
• Typically 4–6 years of relevant experience in data engineering or platform delivery.
• Hands‑on experience developing scalable data solutions using Python, SQL, and R.
• Experience with data pipelines, streaming architectures, and big data ecosystems.
• Cloud computing architecture, data architecture design and modelling.
• Strong communication and stakeholder management skills.

Responsibilities

• Lead workstream delivery and ensure quality across processes.
• Engage with clients daily, identify opportunities for services.
• Design scalable data architectures and production‑ready pipelines.
• Manage budgets and engagement economics; guide cross‑functional teams.

Skills

Python

SQL

R

Data pipelines

Big data ecosystems

Cloud platforms (AWS/Azure)

Data architecture

Stakeholder collaboration

GenAI tools

Project leadership

Education

Bachelor’s degree in Data Science / CS / Analytics

Tools

Cloud Platforms (AWS/Azure)

ETL/Data integration tools

Job description

EY in the United States seeks a Data Engineering Manager to lead AI‑driven data platform initiatives. You will design scalable data architectures and production pipelines, collaborating with data scientists, engineers, and clients to align technical outcomes with business needs.

You will oversee cross‑functional teams, manage budgets, and ensure quality while delivering trusted data insights and value for stakeholders.