Forward-Deployed Data Engineer for AI Pipelines

EY; Memphis (TN); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k) plans

Generous paid time off

Job summary

EY’s Office of the CTO is seeking a Data Engineer to join the Advanced Forward Engineering (AFE) team. You’ll embed with client delivery pods to ensure data is accessible, governed, and production-ready for AI solutions in regulated environments.

You’ll own data readiness, design robust pipelines, and collaborate with forward deployed engineers to deliver durable interfaces while navigating data governance and compliance constraints.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 5+ years of experience in data engineering, data integration, or analytics engineering.
• 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

Kafka

Flink

Spark

Azure Data Factory

Education

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

Tools

Kafka

Flink

Spark

Azure Data Factory

Job description

EY’s Office of the CTO is seeking a Data Engineer to join the Advanced Forward Engineering (AFE) team. You’ll embed with client delivery pods to ensure data is accessible, governed, and production-ready for AI solutions in regulated environments.

You’ll own data readiness, design robust pipelines, and collaborate with forward deployed engineers to deliver durable interfaces while navigating data governance and compliance constraints.