Senior Data Engineer – AI-Driven Data Pipelines (Hybrid)

EY; Seattle (WA); On-site; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid/Remote-friendly work model

Medical and dental coverage

Pension and 401(k) plans

Paid time off

Job summary

EY is seeking a Data Engineer to join the Advanced Forward Engineering team, embedding with client delivery pods to ensure data is accessible, governed, and production-ready for AI deployments in regulated environments.

You’ll own data readiness, design ingestion and transformation patterns, enforce governance, and collaborate with Forward Deployed Engineers to enable reliable AI workflows from development to production.

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 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

5+ years data engineering

Data pipelines in cloud/hybrid

Relational databases & warehouses

Data governance & security

Collaborate with engineers

Clear communication

API-based data access

Strong problem solving

Regulated environments experience

Education

Bachelor's or Master's in CS or related field

Tools

Postgres

Oracle

Databricks

Snowflake

BigQuery

Redshift

Azure Data Factory

Kafka

Flink

Spark

Job description

EY is seeking a Data Engineer to join the Advanced Forward Engineering team, embedding with client delivery pods to ensure data is accessible, governed, and production-ready for AI deployments in regulated environments.

You’ll own data readiness, design ingestion and transformation patterns, enforce governance, and collaborate with Forward Deployed Engineers to enable reliable AI workflows from development to production.