Forward-Deployed Data Engineer for AI Pipelines

EY; Irvine (CA); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

401(k) plan

Job summary

EY seeks a Data Engineer for the Advanced Forward Engineering team to embed with client environments and ensure data readiness for AI deployments. You will own data pipelines, enforce governance, and deliver robust interfaces in regulated settings.

The role blends data engineering with delivery execution, working with engineers and client stakeholders to translate complex data landscapes into dependable, compliant AI-enabled solutions. Hybrid work model with client engagements across industries.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related technical field.
• 5+ years of experience in data engineering, data integration, or analytics engineering roles.
• Hands-on experience building and operating data pipelines in cloud or hybrid environments.
• Experience integrating with relational databases, data warehouses, data lakes, or enterprise systems.
• Familiarity with data modeling, transformation frameworks, and API-based data access.
• Experience working under data governance, security, or compliance constraints.
• Ability to collaborate closely with application engineers and operate in delivery-focused teams.

Responsibilities

• Serve as the data owner within an AFE delivery pod, ensuring data readiness does not block or delay delivery outcomes.
• Design and implement data ingestion, transformation, and access patterns that integrate AI systems with client and legacy data sources.
• Ensure data pipelines comply with governance, security, lineage, and access control requirements mandated by regulated environments.
• Implement data interfaces and contracts that satisfy DevOps Specification (DS) data requirements for supported deployment templates.
• Partner closely with Forward Deployed Software Engineer roles to enable AI workflows, retrieval, and analytics that are reliable in production.
• Diagnose and resolve data quality, schema drift, and integration issues encountered in real deployment scenarios.
• Contribute reusable data patterns and implementation learnings back to the AFE integration core to improve repeatability across pods.
• Support validation, testing, and deployment activities to ensure data flows behave correctly and consistently across environments (dev, test, pre-prod, prod).

Skills

Data engineering

Governance

APIs

Data modeling

Legacy data integration

Communication

Ambiguity handling

Regulatory compliance

Production systems

Data interfaces

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

Postgres

Oracle

Databricks

Snowflake

BigQuery

RedShift

Azure Data Factory

Kafka

Flink

Spark

Job description

EY seeks a Data Engineer for the Advanced Forward Engineering team to embed with client environments and ensure data readiness for AI deployments. You will own data pipelines, enforce governance, and deliver robust interfaces in regulated settings.

The role blends data engineering with delivery execution, working with engineers and client stakeholders to translate complex data landscapes into dependable, compliant AI-enabled solutions. Hybrid work model with client engagements across industries.