Data Engineering Manager: AI & Analytics Platform Leader

EY; Palo Alto (CA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off options

Job summary

EY is seeking a data-focused product and platform leader to design and deliver AI-powered analytics solutions for diverse clients. The role involves building scalable data architectures, collaborating with data scientists, engineers, and business stakeholders to align technical work with business goals.

You will guide data strategy, model deployment, and production handoffs while managing client relationships and project delivery in a hybrid work environment.

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.

Responsibilities

• Ingenius leading workstreams and ensuring quality across processes.
• Engaging with clients daily, participating in working sessions, and identifying opportunities for additional services.
• Implementing resource plans and budgets while managing engagement economics.

Skills

Python

R

SQL

Data engineering

Cloud architecture

Data modeling

Data integration

Data security

Ontology design

Software engineering

Data quality

Database management

Semantic layer

Leadership

Stakeholder management

Cross-functional collaboration

Change management

Education

Bachelor’s degree in Data Science, Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Applied Math, Analytics, or related preferred.

Job description

EY is seeking a data-focused product and platform leader to design and deliver AI-powered analytics solutions for diverse clients. The role involves building scalable data architectures, collaborating with data scientists, engineers, and business stakeholders to align technical work with business goals.

You will guide data strategy, model deployment, and production handoffs while managing client relationships and project delivery in a hybrid work environment.