Senior Data Engineer: AI-Ready in Regulated Environments

EY; Charleston (WV); Hybrid; USD 107,000 - 201,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation and benefits

Job summary

EY’s Advanced Forward Engineering team is seeking a Data Engineer to join AFE delivery pods, embedding with client environments to ensure AI systems are data-ready, governed, and production-ready. You’ll work at the intersection of data engineering, delivery execution, and regulatory constraints, translating complex data landscapes into dependable solutions.

You’ll partner with Forward Deployed Engineers to enable AI workflows and analytics, while ensuring data quality and compliance across dev,

Qualifications

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

Data integration

Cloud data pipelines

Governance & security

Communicator

Legacy data

Ambiguity handling

Education

Bachelors/Masters in CS or related field

Tools

Postgres

Oracle

Databricks

Snowflake

BigQuery

Redshift

Azure Data Factory

Kafka

Flink

Spark

Job description

EY’s Advanced Forward Engineering team is seeking a Data Engineer to join AFE delivery pods, embedding with client environments to ensure AI systems are data-ready, governed, and production-ready. You’ll work at the intersection of data engineering, delivery execution, and regulatory constraints, translating complex data landscapes into dependable solutions.

You’ll partner with Forward Deployed Engineers to enable AI workflows and analytics, while ensuring data quality and compliance across dev,