Lead Data Architect

Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes. We are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy. Lead Data Architect Location: Suitland, MD (Hybrid) Terms: Full-time Clearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required Travel: % Project Description This position supports Revolutional'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. The core challenge is orchestrating complex, multi‑contractor delivery while transforming both technology and operating models without disrupting mission‑critical operations. Position Description As a Lead Data Architect at Revolutional, 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. 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 Technical Environment Cloud‑native data platforms (AWS, Azure) Data lakes, lakehouse architectures, warehouses, marts, and distributed analytics ecosystems Big data and streaming technologies (Spark, Kafka, Databricks, Snowflake, Airflow) APIs, event‑driven architectures, and distributed integration platforms ETL/ELT pipelines and large‑scale data processing frameworks MLOps, AI/ML‑enabled analytics, and model deployment environments Infrastructure‑as‑Code and automation tools (Terraform) DevSecOps pipelines and CI/CD automation frameworks Data governance, metadata, lineage, and catalog platforms Agile and scaled Agile (SAFe) delivery environments Delivery and collaboration platforms (Git, Jira, Confluence) Baseline Requirements U.S. Citizenship with the ability to obtain a Public Trust 10‑14+ 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 Ability to obtain and maintain a Public Trust clearance Technical Capabilities 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 Core Strengths Strategic thinker capable of translating mission and business requirements into scalable enterprise data architectures Strong ownership mindset with accountability for architecture, governance, and operational outcomes Ability to influence technical direction across engineering, analytics, architecture, and operational teams Strong decision‑making skills balancing modernization goals, operational realities, and compliance requirements Effective communication across technical, operational, and executive stakeholders Ability to coordinate delivery and governance across complex, multi‑team, multi‑contractor environments Nice to Have (Differentiators) 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 Benefits Traditional and HSA‑eligible medical insurance plans 100% employer‑paid dental and vision insurance options 100% employer‑sponsored STD, LTD, and life insurance 5% 401(k) company matching Flexible schedules and teleworking options Paid holidays and PTO accrual plans Paid parental leave Professional development and career growth opportunities Team and company‑wide events, recognition, and appreciation Equal Opportunity Employer Revolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender, gender identity, sexual orientation, disability, or genetics. Revolutional does and will take affirmative action to employ and advance in employment individuals with disabilities and protected veterans. To perform the above job successfully, an individual must possess the knowledge, skills, and abilities listed; meet the education and work experience required; and must be able to perform each essential duty and responsibility satisfactorily. Other duties in addition to those listed may be assigned as necessary to meet business needs. Reasonable accommodation will be made to enable an applicant with a disability to successfully apply for and/or perform the essential duties of the job. #J-18808-Ljbffr