Senior Data Architect

Overview

Tanaq Technical Services (TTS), a division of St. George Tanaq (SGT) Corporation, is an 8(a) Alaskan Native Small Business that specializes in delivering Enterprise Integrated Technology Solutions and Support Services to the Federal Government. TTS’s innovative approach combines proactive strategies, efficient processes, and emerging technologies to deliver seamless, integrated services for our clients. TTS prides itself in being Mission Driven and People Focused.

We are seeking a Senior Data Architect to support the Department of Housing and Urban Development’s Office of the Chief Information Officer (HUD OCIO). The Senior Data Architect serves as the enterprise level authority responsible for shaping and governing the data architecture that underpins the agency’s artificial intelligence, analytics, and cloud modernization strategy.

• 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.
• 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.
• Partner with AI/ML teams to design data pipelines, feature stores, and model-ready datasets.
• Advise senior leadership on data strategy, modernization roadmaps, and emerging technologies.
• 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.

• 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, along with MDM, deduplication, and PII minimization or tokenization.
• Event-driven and CDC-based architectures to decouple legacy systems, familiarity with analytical and vector data stores.
• Compliance with FISMA and FedRAMP requirements, including comprehensive logging, auditability, and 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.

• Cloud platforms:
  Azure and AWS.
• Cloud Native Services: AWS Bedrock, Azure OpenAI, S3, Redshift, Data Factory.
• Deep knowledge of relational, No
  
  SQL, 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/Git Hub/Git Lab.
• Data governance, metadata management, and logging.
• Proven experience designing and governing enterprise data architectures in complex, multi-system environments.