Lead Data Architect

Lead Data ArchitectThis 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: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations.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.This role requires someone who can balance long-term data strategy with operational delivery realities, while establishing architecture standards that support scalability, compliance, resiliency, and real-time data operations.Provide technical leadership across enterprise data architecture efforts within a large-scale modernization programDesign and govern scalable data ecosystems including data lakes, lakehouse architectures, data warehouses, marts, and distributed processing platformsDefine and implement enterprise data models, schemas, standards, retention strategies, and lifecycle management approachesOversee data management, integration, quality, lineage, storage, retention, and governance processes across systemsEstablish metadata management, data catalogs, data dictionaries, and lineage frameworks supporting governance and traceability requirementsDesign and manage large-scale data ingestion, ETL/ELT pipelines, transformation workflows, analytics, and dissemination capabilitiesSupport real-time and streaming architectures using event-driven processing and distributed messaging systemsDesign 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 RMFCollaborate with application architects, engineers, data scientists, SMEs, and external vendors to deliver secure, scalable, and high-performing data solutionsEnsure compliance with federal data management, privacy, and security requirements including NIST, FedRAMP, Zero Trust, ATO processes, encryption, access control, and data sharing standardsLead architecture efforts supporting system-of-systems (SoS) integrations across multiple contractors, vendors, and interdependent platformsImplement FinOps and cloud optimization strategies including cost monitoring, tagging, performance tuning, and operational efficiency improvementsSupport 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 teamsMentor architects and engineering teams while promoting consistency, governance, and technical excellenceCloud-native data platforms (AWS, Azure)Data lakes, lakehouse architectures, warehouses, marts, and distributed analytics ecosystemsBig data and streaming technologies (Spark, Kafka, Databricks, Snowflake, Airflow)APIs, event-driven architectures, and distributed integration platformsETL/ELT pipelines and large-scale data processing frameworksMLOps, AI/ML-enabled analytics, and model deployment environmentsInfrastructure-as-Code and automation tools (Terraform)DevSecOps pipelines and CI/CD automation frameworksData governance, metadata, lineage, and catalog platformsAgile and scaled Agile (SAFe) delivery environmentsDelivery and collaboration platforms (Git, Jira, Confluence)Baseline RequirementsU.S. Citizenship with the ability to obtain a Public Trust10–14+ years of experience in data architecture, enterprise data engineering, or large-scale modernization initiativesProven experience designing enterprise data architectures for large-scale, distributed systems environmentsExperience operating within Agile and SAFe/scaled Agile delivery frameworksAbility to obtain and maintain a Public Trust clearanceTechnical CapabilitiesStrong experience designing enterprise data ecosystems including data lakes, warehouses, marts, and distributed data platformsExperience with large-scale data ingestion, ETL/ELT pipelines, analytics, dissemination, and real-time processing architecturesExperience implementing metadata management, lineage, catalogs, and governance frameworksExperience with system-of-systems integration, APIs, interface management, and distributed architecturesExperience supporting AI/ML-enabled environments including MLOps, ML pipelines, model deployment, and AI governanceExperience with open-source and modern data stack technologies including Spark, Kafka, Airflow, Databricks, and SnowflakeExperience implementing data governance, data quality, data classification, tagging, privacy, and enterprise sharing frameworksExperience with cloud-native data services across AWS and Azure environmentsExperience implementing DevSecOps practices, CI/CD pipelines, and infrastructure automationStrong understanding of federal security and compliance frameworks including NIST, FedRAMP, Zero Trust, encryption, access controls, and ATO supportExperience with FinOps, cloud cost optimization, and performance tuning of enterprise data platformsExperience supporting operational monitoring, maintenance, and lifecycle management of enterprise data systemsCore StrengthsStrategic thinker capable of translating mission and business requirements into scalable enterprise data architecturesStrong ownership mindset with accountability for architecture, governance, and operational outcomesAbility to influence technical direction across engineering, analytics, architecture, and operational teamsStrong decision-making skills balancing modernization goals, operational realities, and compliance requirementsEffective communication across technical, operational, and executive stakeholdersAbility to coordinate delivery and governance across complex, multi-team, multi-contractor environmentsNice to Have (Differentiators)Certifications in cloud data platforms, big data technologies, or enterprise architecture frameworksExperience supporting statistical and similarly large-scale federal modernization programsExperience with large-scale real-time analytics or event-streaming environmentsExperience implementing enterprise AI governance or advanced analytics frameworksExperience supporting DataOps or platform engineering initiatives