Forward-Deployed Data Engineer for AI in Regulated Settings

EY; Arlington (VA); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Total rewards package including health

Generous paid time off

Job summary

EY’s Advanced Forward Engineering team seeks a Data Engineer to join delivery pods embedded with clients. You will own data readiness, design ingestion and transformation patterns, and ensure governance and security across regulated environments.

You will collaborate with other engineers to enable AI workflows, diagnose data issues, and contribute reusable data patterns for repeatable deployments in production.

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

Data governance

Data pipelines

Cloud environments

Communication

Problem solving

Regulated environments

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Postgres

Oracle

Databricks

Snowflake

BigQuery

Redshift

Azure Data Factory

Kafka

Flink

Spark

Job description

EY’s Advanced Forward Engineering team seeks a Data Engineer to join delivery pods embedded with clients. You will own data readiness, design ingestion and transformation patterns, and ensure governance and security across regulated environments.

You will collaborate with other engineers to enable AI workflows, diagnose data issues, and contribute reusable data patterns for repeatable deployments in production.