Data Engineering Manager - AI/Analytics Platform Lead

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

Benefits offered by this job

Hybrid work model

Flexible vacation policy

Competitive compensation and benefits

Job summary

EY is seeking a Data Engineering Manager to design and build AI and analytics solutions. You will lead scalable data architectures, collaborate with data professionals, management, and stakeholders to align technical and business needs. Travel may be required, and you will guide teams through end-to-end data lifecycles.

The role emphasizes hands-on coding, responsible data practices, and delivering measurable business value in a hybrid work environment.

Qualifications

• Bachelor’s degree in a data-related field or equivalent.
• Typically 4–6 years of relevant experience.
• Hands-on experience developing scalable data solutions using Python, R, and SQL.
• Cloud computing architecture knowledge.
• Data architecture design and modelling.
• Data integration and data security awareness.
• Software engineering practices and versioned code.

Responsibilities

• Lead workstream delivery with quality across processes.
• Engage with clients daily; identify opportunities for additional services.
• Implement resource and budgets; manage engagement economics.

Skills

Stakeholder management

GenAI tooling

Cross-functional

Ambiguity handling

End-to-end data projects

Data quality checks

Software engineering

Analytical skills

Communication

Project management

Relationship management

Education

Bachelor’s degree in Data Science/CS/ML

Tools

Python

R

SQL

Cloud Platforms

Data Pipelines

Job description

EY is seeking a Data Engineering Manager to design and build AI and analytics solutions. You will lead scalable data architectures, collaborate with data professionals, management, and stakeholders to align technical and business needs. Travel may be required, and you will guide teams through end-to-end data lifecycles.

The role emphasizes hands-on coding, responsible data practices, and delivering measurable business value in a hybrid work environment.