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Peraton

Runs and secures technology for federal agencies

Lead Data Architect

Data ManagementConfirmed live in the last 24 hours
Full-timeSuitland-Silver Hill, MD, USA

About the Job

Requirements

  • A bachelor's degree and 12 years of experience, an associate's degree and 14 years of experience, or a high school diploma/equivalent and 16 years of experience.
  • Must be a U.S. citizen and able to obtain a Public Trust clearance.
  • At least 10 years of experience in data architecture, enterprise data engineering, or large-scale modernization initiatives.
  • Proven experience designing enterprise data architectures for large-scale distributed systems environments.
  • Experience working within Agile and SAFe/scaled Agile delivery frameworks.
  • Strong experience designing enterprise data ecosystems, including data lakes, warehouses, marts, and distributed data platforms.
  • Experience with large-scale data ingestion, ETL/ELT pipelines, analytics, dissemination, and real-time processing architectures.
  • Experience implementing metadata management, lineage, catalogs, and governance frameworks.
  • Experience with system-of-systems integration, APIs, interface management, and distributed architectures.
  • Experience supporting AI/ML-enabled environments, including MLOps, ML pipelines, model deployment, and AI governance.
  • Experience with Spark, Kafka, Airflow, Databricks, Snowflake, and modern data stack technologies.
  • Experience implementing data governance, data quality, data classification, tagging, privacy, and enterprise sharing frameworks.
  • Experience with cloud-native data services across AWS and Azure.
  • Experience implementing DevSecOps practices, CI/CD pipelines, and infrastructure automation.
  • Strong understanding of federal security and compliance frameworks, including NIST, FedRAMP, Zero Trust, encryption, access controls, and ATO support.
  • Experience with FinOps, cloud cost optimization, and performance tuning of enterprise data platforms.
  • Experience supporting operational monitoring, maintenance, and lifecycle management of enterprise data systems.

Responsibilities

  • Provide technical leadership across enterprise data architecture efforts within a large-scale modernization program.
  • Design and govern scalable data ecosystems, including data lakes, lakehouse architectures, data warehouses, marts, and distributed processing platforms.
  • Define and implement enterprise data models, schemas, standards, retention strategies, and lifecycle management approaches.
  • Oversee data management, integration, quality, lineage, storage, retention, and governance processes across systems.
  • Establish metadata management, data catalogs, data dictionaries, and lineage frameworks supporting governance and traceability requirements.
  • Design and manage large-scale data ingestion, ETL/ELT pipelines, transformation workflows, analytics, and dissemination capabilities.
  • Support real-time and streaming architectures using event-driven processing and distributed messaging systems.
  • Design and oversee APIs, system interconnections, interface management processes, and Interface Control Documents.
  • Support AI/ML-enabled architectures, including ML pipelines, MLOps processes, model deployment, and AI governance frameworks such as the NIST AI RMF.
  • Collaborate with application architects, engineers, data scientists, subject matter experts, and external vendors to deliver secure, scalable, and high-performing data solutions.
  • Ensure compliance with federal data management, privacy, and security requirements, including NIST, FedRAMP, Zero Trust, ATO processes, encryption, access control, and data sharing standards.
  • Lead architecture efforts supporting system-of-systems integrations across multiple contractors, vendors, and interdependent platforms.
  • Implement FinOps and cloud optimization strategies, including cost monitoring, tagging, performance tuning, and operational efficiency improvements.
  • Support operational management of enterprise data platforms, including monitoring, maintenance, performance optimization, and lifecycle management.
  • Establish and enforce architecture governance, standards, and best practices across Agile and SAFe delivery teams.
  • Mentor architects and engineering teams while promoting consistency, governance, and technical excellence.

Desired Qualifications

  • Certifications in cloud data platforms, big data technologies, or enterprise architecture frameworks.
  • Experience supporting statistical and similarly large-scale federal modernization programs.
  • Experience with large-scale real-time analytics or event-streaming environments.
  • Experience implementing enterprise AI governance or advanced analytics frameworks.
  • Experience supporting DataOps or platform engineering initiatives.

About the Company

Peraton

Runs and secures technology for federal agencies

Peraton builds and runs secure technology for American defense, intelligence, space, and civilian agencies, from military networks to satellite ground stations. In 2025, the Federal Aviation Administration chose it to manage the overhaul of the nation's air traffic control system, replacing copper wiring with fiber and upgrading radar and radios. Its engineers, many holding security clearances, run and defend agency networks and data centers, write mission software, and operate space and communications systems, and agencies pay for this work through multiyear contracts. Peraton was formed in 2017, when private-equity firm Veritas Capital bought Harris Corporation's government IT business, and is based in Reston, Virginia.

Company size
10,001+
Company stage
Grant
Total funding
$60M
Headquarters
Reston, VA
Founded
2017

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