Data Engineer, AI Platforms & Client Impact

EY; Baltimore (MD); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Job summary

EY is seeking a data-focused leader to drive mission-critical platforms and intelligent data solutions. You will guide cross-functional teams, manage client engagements, and shape product outcomes across AI-centric platforms.

The role emphasizes hands-on data engineering, scalable pipelines, cloud architectures, and collaboration with clients and stakeholders to deliver measurable value.

Qualifications

• Bachelor’s degree in Data Science, Machine Learning, CS, Statistics, Math, 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.
• 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

Data Engineering

Data Pipelines

Big Data

Cloud Computing

Stakeholder Management

GenAI tooling

Education

Bachelor’s degree in Data Science, CS, or related

Tools

Python

R

SQL

Cloud Platforms

Job description

EY is seeking a data-focused leader to drive mission-critical platforms and intelligent data solutions. You will guide cross-functional teams, manage client engagements, and shape product outcomes across AI-centric platforms.

The role emphasizes hands-on data engineering, scalable pipelines, cloud architectures, and collaboration with clients and stakeholders to deliver measurable value.