Enterprise Architect- Data Infrastructure ETL

Role Overview

Due to the client contract, you will be assigned, this position requires you to be a U.S. citizen

The Enterprise Architect provides expertise on the design and participates in building of data infrastructure to optimize data processing from a variety of data sources. They Independently design and implement data governance policies and procedures for data handling to manage data consistency, integrity, accuracy, and reliability. Provides expertise on and participates in the design and implementation of rigorous data validation and integrity checks, proactively mitigating data quality issues that could impact data pipeline and model performance.

This role will also leverage advanced knowledge of Extract, Transform, and Load (ETL) processes to design, develop, and optimize automated, scalable, and efficient data pipeline architectures to build reusable data products.

Work independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug advanced data solutions that are scalable, efficient, cost effective, and reliable

Leads interface testing and integration validation for complex Oracle Health implementations. This role owns the coordination of multiple concurrent interface workstreams—including schedules, status, dependencies, risks, issues, and escalations—to ensure integration deliverables are tested, ready, and aligned with deployment timelines.

As a client-facing leader, the architect facilitates meetings, communicates clearly with VA stakeholders and technical teams, drives decisions and follow-up actions, and serves as a trusted advisor throughout the testing lifecycle. The ideal candidate understands electronic health record workflows, HL7 messaging, and healthcare data exchange across clinical, ancillary, and external systems.

Requirements:

• 8+ years of experience in data engineering, integration architecture, or related technical roles , with advanced expertise designing, building, and optimizing scalable data infrastructure, ETL pipelines, data flows, and reusable data products across diverse data sources.
• Strong expertise in data quality and governance , including designing and implementing data validation, integrity checks, governance policies, data handling standards, and automated controls to ensure data accuracy, consistency, reliability, and compliance.
• Demonstrated experience with healthcare systems integration and interface testing , including knowledge of electronic health record (EHR) workflows, HL7 messaging, healthcare data exchange, and integration across clinical, ancillary, and external systems; Oracle Health implementation experience preferred.
• Due to the client contract, you will be assigned, this position requires you to be a U.S. citizen
• Proven ability to lead complex integration and testing workstreams , managing concurrent schedules, dependencies, risks, issues, escalations, SLAs, and deployment

Responsibilities

Data Processing & Pipelining – Data Requirements, Collection, and Infrastructure:

• Provides expertise on the design and participates in building of data infrastructure to optimize data processing from a variety of data sources.
• Independently analyzes, designs, and troubleshoots data flows based on business needs.
• Participates and designs architecture, performance, and security reviews of the technical solution.
• Adjusts data collection processes that involve indexing and query optimizations for optimal performance.
• Builds Extract, Transform, and Load (ETL) pipelines to support efficient and scalable data collection and extraction.
• Engages with and holds the upstream and downstream teams accountable for the predefined service level agreements (SLAs).

Data Processing & Pipelining – Data Validation & Quality Assurance:

• Provides expertise on and participates in the design and implementation of rigorous data validation and integrity checks, proactively mitigating data quality issues that could impact data pipeline and model performance.
• Mentors less experienced team members to define data annotation and labeling processes to ensure data quality.
• Identifies opportunities for automation of data validation and governance, and implements them.

Data Pipeline and Solutions Engineering – Pipeline Design:

• Leverages advanced knowledge of ETL processes to design, develop, and optimize automated, scalable, and efficient data pipeline architectures to build reusable data products.
• Implements advanced data storage solutions to store the processed data to be used in a scalable, optimized, and efficient way for access and analysis.

Problem Solving:

• Identifies and addresses moderately complex issues by analyzing a wide range of data and/or information to identify solutions in accordance with standard practices.
• Proactively escalates unresolved or critical issues with a thorough assessment and suggests potential solutions.
• Reviews, contributes to, and documents problem solving strategies. #LI-DJ1

Reviews, contributes to, and documents problem solving strategies.

#LI-DJ1

Requirements & Qualifications

Career Level - IC4

Application Instructions

Apply directly on Oracle Careers at Enterprise Architect- Data Infrastructure ETL↗.