Forward-Deployed Data Engineer for AI Production

EY; Palo Alto (CA); Hybrid; USD 128,000 - 201,000; Full time

Job summary

EY is seeking a Data Engineer for the Advanced Forward Engineering team to embed with client environments and ensure data is production-ready for AI solutions. You will own data readiness, design pipelines, and enforce governance while collaborating with delivery engineers to maintain reliability in regulated settings.

You will work across hybrid environments, handle data ingestion, transformation, and access, and help translate ambiguous data landscapes into compliant, durable interfaces for AI

Qualifications

• Bachelor’s or Master’s degree in Computer Science or 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

Postgres

Oracle

Databricks

SnowFlake

BigQuery

RedShift

Azure Data Factory

Kafka

Flink

Spark

Data modeling

API-based data access

Data governance

Education

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

Tools

Postgres

Oracle

Databricks

SnowFlake

BigQuery

RedShift

Azure Data Factory

Kafka

Flink

Spark

Job description

EY is seeking a Data Engineer for the Advanced Forward Engineering team to embed with client environments and ensure data is production-ready for AI solutions. You will own data readiness, design pipelines, and enforce governance while collaborating with delivery engineers to maintain reliability in regulated settings.

You will work across hybrid environments, handle data ingestion, transformation, and access, and help translate ambiguous data landscapes into compliant, durable interfaces for AI