Data Architect

Data Architect

The Data Architect sets the technical direction for how mission data is structured, stored, governed, and consumed across the customer's analytic systems. They design integrated data models, evaluate platform and BI tooling, and ensure the analytic ecosystem aligns with federal Enterprise Architecture, NIEM, and federal compliance mandates. They are a top-level technical contributor and a key partner to data engineers, data scientists, and business stakeholders.

Responsibilities:

• Develop and maintain enterprise and solution-level data architectures — conceptual, logical, and physical models — for integrated, shared systems.
• Evaluate and recommend systems architecture, BI tooling, design patterns, quality and performance standards, and physical/cloud-based data structures.
• Develop strategies for warehouse and lakehouse implementation, data acquisition and access, archive, and recovery.
• Define structures, attributes, and nomenclature of data elements; build and curate data dictionaries, glossaries, and metadata.
• Evaluate new data sources for quality and integration fitness; partner with the customer's data management office on submissions to relevant Data Reference Models and Enterprise Architecture repositories.
• Ensure conformance with federal Enterprise Architecture, NIEM, agency Data Management Policy, DHS 4300A/B/C or equivalent, FIPS 140-2 / FIPS 197, HSPD-12 PIV, IPv6 (USGv6), and Section 508.
• Provide expertise in system architecture, design, and systems-management processes; advise on technology insertion (TI) trade studies.
• Partner with data scientists on feature stores, model registries, and reproducibility patterns.

Requirements:

• Must have an active Top Secret clearance.
• Six (6)+ years of relevant experience in data architecture, computer science, engineering, or information systems applied to data science research or big data analytics.
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related technical discipline. (A Master's may substitute for up to two years of experience; a Ph.D. for up to five.)
• Ability to perform functional and data requirements analysis and implement data architecture projects.
• Demonstrated knowledge of information architecture methodologies.
• Ability to lead development of organization-wide data architectures for integrated, shared software and database systems.

Preferred Qualifications:

• Experience with NIEM and federal data exchange standards (BPMN 1.1/2.0, UML2).
• Experience designing data mesh, data fabric, or domain-oriented data architectures.
• Hands-on experience with modern lakehouse platforms (Databricks, Snowflake, Iceberg, Delta Lake).
• Experience with data governance and catalog tooling (Collibra, Alation, Atlan, AWS Glue Data Catalog, Microsoft Purview).
• Experience implementing zero-trust and FedRAMP-aligned data architectures.
• TOGAF, AWS Solutions Architect, Azure Solutions Architect, or comparable certification.

Tools & Technologies:

• Modeling: ER/Studio, erwin, PowerDesigner; Lucidchart / Visio; BPMN 2.0, UML2.
• Cloud: AWS GovCloud, Azure Government.
• Lakehouse / warehouse: Databricks, Snowflake, Synapse, Redshift, Delta Lake, Iceberg.
• Catalog & governance: Collibra, Alation, Atlan, AWS Glue Data Catalog, Microsoft Purview.
• Standards: NIEM, FEA, FIPS 140-2 / 197, HSPD-12 PIV, IPv6 (USGv6).
• Languages: SQL, Python (familiarity).