Senior Data Engineer - AI Pipelines in Regulated Environments

EY; Houston (TX); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Job summary

EY is seeking a Data Engineer to join its Advanced Forward Engineering team and work in forward-deployed pods with client environments. You will ensure data readiness and design scalable data ingestion and transformation patterns to enable AI deployments, while maintaining governance and reliability.

The role emphasizes collaboration with delivery engineers and managing data in complex, regulated environments across cloud/hybrid setups.

Qualifications

• Bachelor's or Master's degree in Computer Science or related technical 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 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

Education

Bachelor's or Master's degree in Computer Science

Tools

Cloud platforms (AWS/GCP/Azure)

Job description

EY is seeking a Data Engineer to join its Advanced Forward Engineering team and work in forward-deployed pods with client environments. You will ensure data readiness and design scalable data ingestion and transformation patterns to enable AI deployments, while maintaining governance and reliability.

The role emphasizes collaboration with delivery engineers and managing data in complex, regulated environments across cloud/hybrid setups.