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Tanaq Technical Services · 19 hours ago

Senior Data Architect

United States

Full-time

Remote

Senior Level

7+ years exp

Tanaq Technical Services (TTS) is an 8(a) Alaskan Native Small Business specializing in delivering Enterprise Integrated Technology Solutions and Support Services to the Federal Government. The Senior Data Architect role involves shaping and governing the data architecture for the Department of Housing and Urban Development, focusing on artificial intelligence, analytics, and cloud modernization strategies.

Computer Software

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Define and lead the agency’s enterprise data architecture strategy supporting AI, analytics, and cloud modernization

Architect cloud-native data platforms and oversee the modernization of legacy data systems into secure, scalable environments

Develop and maintain enterprise data models and standards that ensure interoperability across programs and systems

Lead agency-wide data governance initiatives, including metadata management, data lineage, quality frameworks, and stewardship

Lead and partner with AI/ML teams to design data pipelines, feature stores, and model-ready datasets that support advanced analytics

Advise senior leadership on data strategy, modernization roadmaps, and emerging technologies relevant to mission needs

Ensure compliance with federal security and privacy requirements, including FISMA, FedRAMP, NIST, and the Privacy Act

Establish and enforce enterprise data integration patterns, APIs, and interoperability standards

Lead cross-functional working groups and serve as the technical authority for data architecture decisions

Mentor data engineers, analysts, and junior architects, fostering a culture of technical excellence

Configure and manage AI/ML-ready cloud infrastructure (AWS Bedrock, Azure OpenAI)

Oversee the development of data catalogs, master data management (MDM) solutions, and enterprise data services

Qualification

Data architectureCloud-native data systemsAI/ML pipelinesMetadata managementData governanceAWSAzurePythonSQLCommunication skillsProblem-solving

Required

7+ years of experience in data architecture, enterprise architecture, or large-scale data engineering

Enterprise data modeling spanning grants, housing, and broader program domains

Metadata, lineage, and governance implemented through policy-as-code approaches

Design of an AI-ready knowledge layer, including document and record schemas, embedding and RAG strategies, and explainability metadata

Implementation of access, retention, and privacy controls using ABAC/RBAC models and Zero Trust principles

Lakehouse architectures and data-contract patterns (e.g., Delta/Iceberg, schema registries), along with MDM, deduplication, and PII minimization or tokenization

Event-driven and CDC-based architectures to decouple legacy systems (e.g., LRS), with familiarity in both analytical and vector data stores

Compliance with FISMA and FedRAMP requirements, including comprehensive logging, auditability, and production of ATO evidence

Expertise in cloud-native data systems and large-scale data processing

Design and implement AI/ML pipelines, reproducible workflows, and federal compliant systems

Ability to pass required Federal background screening and obtain and maintain both government clearance and customer approval

Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Cloud platforms: Azure and AWS

Cloud Native Services: AWS Bedrock, Azure OpenAI, S3, Redshift, Data Factory

Deep knowledge of relational, NoSQL, and distributed data systems

Strong experience with ETL/ELT frameworks: Airflow, Spark, Databricks, data integration patterns, and API-driven architectures

Demonstrated experience supporting AI/ML initiatives and understanding of model lifecycle data needs

Data modeling, schema design, and optimization for AI workloads

Programming: Python, SQL, Scala, PySpark, Java, Terraform, Kafka, JSON, Bash/Powershell

Version control: Git/GitHub/GitLab

Data governance, metadata management, and logging

Proven experience designing and governing enterprise data architectures in complex, multi-system environments

Exceptional communication skills to work with and collaborate with senior stakeholders, Program Managers, Project Managers, Data Scientists, DevOps, and UX teams

Strong command of data governance, metadata management, and data quality frameworks

Problem-solving for scalable AI/ML pipelines and producing quality documentation and reproducible workflows

Experience working within federal agencies or regulated environments with strict compliance requirements

Experience with federal data standards and frameworks (e.g., CDM, FIBF, NIST)

Knowledge of MDM, data virtualization, and knowledge graph technologies

Agile development mindset and iterative improvement

Security, privacy, and compliance awareness

Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field