- Salary
- $131k – $237k
- Location
- 7075 Egg Harbor Township NJ, United States of America · Eagan, MN · Gaithersburg, MD
- Workplace
- Remote, Hybrid, Onsite
- Type
- Full-time
- Department
- Engineering
- Education
- Master
- Source
- Workday
Description
Leidos is seeking an Enterprise Data Architect to join the Air Traffic Business Area within the Homeland Sector, supporting the development of the Leidos Common Automation Platform (L-CAP). L-CAP is a mission-critical, future-ready automation platform built on a hybrid cloud data mesh architecture, enabling next-generation air traffic management capabilities. You will lead enterprise data architecture for a hybrid cloud data mesh platform supporting real-time air traffic management and next-generation aviation services. We are building with an AI-first engineering mindset, embracing emerging AI capabilities and modern development practices to accelerate delivery, improve software quality, and continuously evolve how we design and build mission-critical systems. This position supports government programs and requires the ability to obtain and maintain a favorable Public Trust investigation.
This role is part of a growing program, and hiring will depend on available funding. We review applications on a rolling basis, but the timeline for interviews and offers may vary. In some cases, we may extend contingent offers that become active once funding is confirmed.
This position is located in Gaithersburg, MD; Egg Harbor Township, NJ; or Eagan, MN. This is an opportunity to contribute to projects that impact millions of air travelers.
This is a hybrid position requiring 3 days onsite and 2 days remote work. Candidates should reside a commutable distance to one of the above locations.
What You'll Do
Define the data mesh architecture including domain boundaries and data products
Establish the enterprise data governance framework and standards
Design real-time streaming data pipelines for operational aviation data
Architect event-driven data integration patterns across platform services
Define data product standards including contracts, quality, and discoverability
Develop the data integration strategy across legacy and modern systems
Plan and oversee legacy data migration to the new platform architecture
Establish data quality standards, monitoring, and remediation processes
Coordinate cross-ART data architecture decisions and dependencies
Implement metadata management and data cataloging solutions
Define data architecture for operational ATC data including real-time processing pipelines and low-latency data access patterns
Establish schema governance and data contract management ensuring interoperability across modernized and legacy services
Design latency management strategies for time-critical ATC data flows supporting real-time operational decisions
Implement data lineage tracking providing traceability from source operational systems through processing to consumption
Champion an AI-first engineering culture by identifying and applying AI-assisted development capabilities, automation, and emerging software engineering practices that improve developer productivity, code quality, testing, and delivery.
Core Technical Qualifications:
Bachelor's degree with 12+ years of relevant data architecture experience or 10+ years with a Master's degree or equivalent experience.
Enterprise data architecture leadership for large-scale platforms
Data mesh architecture design and implementation experience
Data governance framework development and enforcement
Event streaming expertise (Apache Kafka or equivalent) at scale
Real-time data pipeline design for mission-critical applications
Expertise across SQL and NoSQL database technologies
Distributed data systems architecture and performance optimization
Advanced data modeling for complex operational domains
Ability to obtain and maintain a Public Trust clearance; US citizenship required; subject to government background investigation
Experience with real-time data processing architectures and low-latency streaming systems
Knowledge of operational data semantics in complex system environments
Experience with schema governance, data contracts, and data lineage implementation
Ability to obtain and maintain a Public Trust
U.S. citizenship required
Successful completion of background investigations as required by the government customer
Preferred / Desired Qualifications
Aviation or FAA data systems experience
Graph database design and implementation
Data lake architecture and governance
Master data management (MDM) strategy and tools
GDPR and data privacy compliance experience
Cloud-native data services (AWS/Azure)
DataOps and data pipeline automation
Experience with ATC or aviation operational data systems and real-time processing requirements
Knowledge of data architecture patterns for safety-critical operational environments
Why Leidos?
You’ll work on systems where performance, precision, and reliability matter — every second. This is not experimental AI for prototypes. This is disciplined, responsible AI applied to mission-critical software that supports national infrastructure.
If you’re excited by solving complex problems in regulated, real-world environments — and using AI as a force multiplier rather than a shortcut — we’d like to talk.
ATMC
If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.
Original Posting:
August 21, 2026For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:
Pay Range $131,300.00 - $237,350.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.