Data Architect

Electrosoft•Arlington, VA

11d•$170,000 - $190,000

About The Position

Electrosoft Services, LLC is an award-winning company that provides comprehensive technology-based solutions and services to federal customers. While cybersecurity is our specialty, we also focus on ICAM, Zero Trust, digital engineering and transformation, and enterprise AI and intelligent automation. We always seek to delight our customers, so we retain highly qualified employees and offer them meaningful work, growth opportunities, and work-life balance. What sets us apart from all other contractors is the sense of teamwork our employees feel – and the knowledge that outstanding effort is recognized and rewarded. The camaraderie we share emanates from Lunch & Learn sessions where we explore new ideas together, fun group activities ranging from escape rooms to miniature golf, and much, much more. If we’ve described you and your dream workplace, please apply and share in the many benefits and opportunities we offer. Data Architect - Senior The Data Architect – Senior Consultant serves as the senior technical authority responsible for the design, governance, implementation, and modernization of enterprise data architectures supporting AI-enabled data management, analytics, and Data-as-a-Service (DaaS) capabilities for the Cybersecurity and Infrastructure Security Agency (CISA). This individual leads the development of scalable, secure, cloud-native data architectures and integration frameworks that enable advanced analytics, artificial intelligence, machine learning, and enterprise decision-making across CISA mission environments. The Data Architect works closely with program leadership, federal stakeholders, data engineers, architects, developers, and analytics teams to ensure enterprise data assets are governed, integrated, optimized, and aligned with DHS and CISA modernization objectives.

Requirements

Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Data Engineering, Software Engineering, Information Technology, Engineering, or a related discipline.
Fifteen (15) years of progressive experience may be substituted in lieu of a degree.
Minimum of ten (10) years of experience in enterprise data architecture, data engineering, database architecture, or advanced data management supporting large-scale enterprise environments.
Demonstrated experience designing AI-ready enterprise data architectures, governed data models, metadata frameworks, and enterprise data standards.
Hands-on experience architecting and optimizing Databricks environments, including Delta Lake, Unity Catalog, Lakehouse architectures, Structured Streaming, and ETL/ELT pipelines.
Experience designing and implementing enterprise cloud architectures utilizing AWS services including S3, IAM, KMS, Lambda, Glue, API Gateway, Aurora, RDS, and related technologies.
Experience implementing enterprise data governance programs, including lineage management, metadata standardization, data quality, semantic modeling, and compliance frameworks.
Experience supporting API-driven architectures, streaming data ingestion, modern integration platforms, and microservices architectures.
Strong understanding of relational and non-relational database technologies and enterprise data management principles.
Experience supporting enterprise analytics, business intelligence, artificial intelligence, and machine learning initiatives.
Experience working in Agile development environments and supporting iterative solution delivery.
Excellent analytical, strategic planning, and problem-solving skills.
Strong written, verbal, and presentation communication abilities.
Ability to communicate effectively with executive leadership, technical teams, and government stakeholders.
U.S. Citizen.
Ability to obtain and maintain a DHS Suitability determination, Public Trust, Secret, or higher security clearance as required by the contract.
At least one Databricks certification, such as: Databricks Certified Data Engineer Professional, Databricks Certified Lakehouse Architect, or Equivalent Databricks certification.
At least one AWS certification, such as: AWS Certified Solutions Architect – Associate, AWS Certified Solutions Architect – Professional, AWS Certified Data Engineer, or Equivalent AWS certification.

Nice To Haves

Experience supporting Department of Homeland Security (DHS) and/or Cybersecurity and Infrastructure Security Agency (CISA) programs.
Experience developing enterprise Data-as-a-Service (DaaS) platforms and cloud-native analytics ecosystems.
Experience supporting enterprise data modernization, cloud migration, and digital transformation initiatives.
Experience implementing metadata-driven architectures, knowledge graphs, ontologies, and enterprise taxonomy frameworks.
Experience supporting artificial intelligence, machine learning, and advanced analytics solutions within Federal environments.
Knowledge of NIST RMF, NIST SP 800-53, FISMA, FedRAMP, Zero Trust, and federal data governance requirements.
Experience supporting large-scale data integration and interoperability initiatives across multiple organizations and systems.
Familiarity with Infrastructure as Code (IaC) tools including Terraform, CloudFormation, or AWS CDK.
Experience leading architecture review boards, governance councils, and enterprise data strategy initiatives.
Relevant certifications such as CDMP, AWS Security Specialty, CISSP, TOGAF, PMP, DAMA Certified Data Management Professional, or equivalent.

Responsibilities

Serve as the lead architect for enterprise data strategy, architecture, governance, and implementation activities supporting AI-enabled data management initiatives.
Design and maintain conceptual, logical, and physical data models that support enterprise analytics, Data-as-a-Service capabilities, AI workloads, and mission operations.
Define enterprise data architecture standards, patterns, frameworks, and best practices.
Lead development of AI-ready data architectures, including unified schemas, governed data models, metadata frameworks, and semantic information structures.
Design, implement, and optimize cloud-native data platforms supporting large-scale structured, semi-structured, and unstructured data environments.
Architect and oversee Databricks Lakehouse environments utilizing Delta Lake, Unity Catalog, ETL/ELT pipelines, Structured Streaming, and enterprise data workflows.
Develop enterprise integration patterns supporting API-based data exchange, microservices integration, event-driven architectures, and streaming ingestion.
Design and implement scalable data pipelines supporting analytics, machine learning, reporting, and operational data services.
Establish enterprise data governance practices, including data stewardship, lineage management, metadata standards, data quality controls, and lifecycle management.
Develop ontology frameworks, taxonomy structures, semantic models, and metadata strategies to improve discoverability, interoperability, and data sharing.
Provide architectural leadership for cloud-native implementations utilizing AWS services and modern data engineering technologies.
Design secure and compliant data environments aligned with Zero Trust, privacy, and cybersecurity requirements.
Support modernization and migration of legacy data systems to scalable cloud architectures.
Develop architecture artifacts including data models, architecture diagrams, governance documentation, reference architectures, and implementation roadmaps.
Collaborate with data engineers, software developers, AI/ML engineers, and business stakeholders to ensure alignment between mission requirements and technical solutions.
Conduct architecture reviews, design assessments, and technical evaluations of data platforms and integration solutions.
Support Agile development activities including sprint planning, backlog refinement, technical reviews, and iterative solution delivery.
Evaluate emerging technologies and provide recommendations for improving scalability, governance, analytics, and AI enablement capabilities.
Support executive briefings, technical presentations, and strategic planning efforts.
Mentor technical teams and provide guidance on enterprise architecture, data governance, and cloud-native data management best practices.
Ensure compliance with DHS, CISA, Federal, and industry standards governing security, privacy, accessibility, and data management.