Lead Data Architect

Peraton; Suitland, Northern (MD, KY); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Peraton seeks an experienced Lead Data Architect to join a federal modernization initiative focused on a data-centric, cloud-native ecosystem. You will drive enterprise data architecture strategy, governance and implementation across a large-scale program.

The role spans data platforms, pipelines, AI/ML integration, and secure, scalable processing across multiple systems. You will mentor architects and engineers while ensuring data is structured, governed, and interoperable across the

Qualifications

• Bachelor's degree with extensive data architecture experience.
• Experience designing enterprise data architectures for large-scale systems.
• Proven background with Agile/SAFe delivery frameworks.
• Experience with data lakes, warehouses, marts and distributed platforms.
• In-depth knowledge of ETL/ELT pipelines and real-time processing.
• Expertise in metadata, lineage, catalogs, and governance.
• Experience with system-of-systems integration and APIs.
• Experience with AI/ML environments including MLOps and governance.

Responsibilities

• Provide technical leadership across enterprise data architecture in a large-scale modernization program.
• Design and govern scalable data ecosystems including lakes, lakehouse, warehouses and marts.
• Define and implement enterprise data models, schemas, standards, retention and lifecycle management.
• Oversee data management, integration, quality, lineage, storage, retention and governance.
• Establish metadata management, data catalogs and lineage frameworks for governance and traceability.
• Design and manage ingestion, ETL/ELT pipelines, analytics and dissemination capabilities.
• Support real-time and streaming architectures using event-driven processing.
• Lead APIs, interface management and ICDs; collaborate across teams and vendors.

Skills

Data architecture

Data engineering

Data governance

Agile/SAFe

MLOps

Cloud data platforms

Data lakes/warehouses

ETL/ELT pipelines

Education

Bachelor's degree

Associates degree

High school diploma

Tools

Spark

Kafka

Airflow

Databricks

Snowflake

Job description

Basic Qualifications:

• Bachelors degree and 12 years of experience or an Associates degree and 14 years of experience or a High School diploma/equivalent and 16 years of experience


• Must be a U.S. Citizen with the ability to obtain a Public Trust clearance


• 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 operating 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 open-source and modern data stack technologies including Spark, Kafka, Airflow, Databricks, and Snowflake


• Experience implementing data governance, data quality, data classification, tagging, privacy, and enterprise sharing frameworks


• Experience with cloud-native data services across AWS and Azure environments


• 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

Preferred 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

Peraton is seeking an experienced Lead Data Architect to join our team of qualified and diverse individuals.

This position supports Peraton's federal customer as part of an application transformation and modernization initiative.

This program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization.

As a Lead Data Architect at Peraton, you will define and drive enterprise data architecture strategy, governance, and implementation across a large-scale federal modernization program.

You will lead architecture efforts spanning data platforms, pipelines, governance frameworks, analytics ecosystems, AI/ML integration, and large-scale distributed processing environments. You will work across multiple systems, teams, vendors, and contractors to ensure data is structured, governed, secured, integrated, and operationalized effectively across the enterprise.

Location: Suitland, MD (Hybrid)

Day to Day Roles and 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 (ICDs)


• 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, SMEs, 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 (SoS) 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 (O&M)


• 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