Solution Architect, Data Governance

Job Title: Solution Architect, Data Governance
Location: Bellevue, WA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Hybrid

Job Description:

About the Role:

• The Solution Architect, Data Governance is a senior technical leadership role responsible for defining, evolving, and governing the end-to-end architecture of Client enterprise Data Governance ecosystem.
• This architect will own the technical vision and integration strategy across a broad and growing platform portfolio - including Open Metadata, Collibra, Ataccama, Securiti.ai, alignment with Fabric Semantic Layer, and a proprietary Metric Catalog - ensuring these platforms operate as a cohesive, scalable, and future-ready governance fabric across Client's data estate.
• This is a strategic and hands-on role that operates at the intersection of enterprise architecture, data platform engineering, and governance program leadership.
• The successful candidate will shape how Client governs data at enterprise scale: designing integration patterns, defining platform standards, guiding AI-assisted governance capabilities, and serving as the architectural authority for governance decisions across engineering, product, and business teams.

What You'll Do:

Governance Platform Architecture & Strategy:

• Own the end-to-end technical architecture for Client's Data Governance platform ecosystem, spanning Open Metadata, Collibra, Ataccama, Securiti.ai, the Semantic Layer, and the Metric Catalog.
• Define and maintain the architectural roadmap for each platform - including integration patterns, data flows, API strategies, scalability plans, and platform evolution - aligned to the broader Data & Intelligence strategy.
• Design the integration architecture connecting governance platforms to T-Client's data infrastructure: Databricks, Unity Catalog, Azure, Microsoft Fabric, DBT, and Power BI.
• Establish and enforce governance platform standards, reference architectures, and technical guardrails that engineering teams follow when building on or extending these platforms.
• Evaluate new technologies, vendors, and open-source frameworks; produce architecture decision records (ADRs) and recommendations for platform evolution.

Open Metadata, Semantic Layer & Metric Catalog Architecture:

• Serve as the architect for Client's Open Metadata deployment - defining ingestion strategies, connector architecture, metadata models, lineage capture patterns, and API integration approaches.
• Architect governance tools and solutions to support the Semantic Layer to serve as a single source of truth for business metrics and KPIs, defining how physical data assets are mapped to semantic definitions consumed by BI tools, AI agents, and downstream applications.
• Design the Metric Catalog architecture - governing how business metrics are defined, versioned, certified, and published across Client's analytics and reporting ecosystem.
• Ensure the three platforms (Open Metadata, Semantic Layer, Metric Catalog) are architecturally coherent and interoperable: certified metrics are registered and discoverable through Open Metadata and the Catalog.

Enterprise Integration & Data Platform Architecture:

• Design scalable metadata ingestion and propagation patterns across Client's 4,000+ applications, ensuring governance platforms receive timely, accurate, and complete metadata at scale.
• Architect event-driven and API-based integration patterns between governance platforms and source systems, data pipelines, and consuming applications.
• Define data lineage architecture end-to-end - from source system through transformation layers (DBT, ADF, PySpark) to consumption - ensuring lineage is captured, stored, and surfaced consistently across the governance ecosystem.
• Partner with Data Engineering and Data Architecture teams to embed governance into platform design - ensuring that new data products, pipelines, and domains are governance-ready from inception.

AI-Assisted Governance Architecture:

• Define the architectural patterns for AI-assisted governance capabilities - including automated data classification, intelligent metadata enrichment, lineage inference, natural language data discovery, and AI-driven data quality - ensuring they integrate cleanly with the governance platform ecosystem.
• Collaborate with AI Engineering teams to design the interfaces between AI agents and governance platforms: how models consume metadata, how outputs are validated and written back, and how human-in-the-loop controls are enforced.
• Architect responsible AI guardrails within the governance platform ecosystem, including audit logging, observability, and explainability requirements for AI-assisted decisions.

Compliance & Security Architecture:

• Ensure the governance platform architecture supports Client's regulatory obligations including CCPA/CPRA, USGCI, FCC requirements, ISO 42001, ISO 27001, and Client's internal TISS-310 data classification standards.
• Architect data access controls, sensitive data handling, and privacy-by-design patterns within governance platforms - including how Securiti.ai integrates with classification, consent, and rights fulfillment workflows.
• Collaborate with Cybersecurity and Privacy Operations teams to ensure governance architecture decisions meet current and emerging compliance requirements.

What You'll Bring:

Education & Experience:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related technical field.
• 10+ years of hands-on experience in data engineering, data architecture, or solution architecture in large-scale enterprise environments.
• Proven track record designing and implementing enterprise-scale data governance or data platform architectures across multiple platforms and organizational domains.

Architecture & Platform Expertise:

• Deep expertise with enterprise Data Governance platforms - including Open Metadata, Collibra, Ataccama, or Securiti.ai - with the ability to architect multi-platform integrations, not just administer individual tools.
• Strong hands-on experience designing Semantic Layer architectures (dbt Semantic Layer, AtScale, Cube.dev, or equivalent) and Metric Catalog solutions.
• Broad expertise across Client's data platform stack or equivalent: Databricks, Unity Catalog, Azure (ADF, ADLS, Synapse), Microsoft Fabric, DBT, and Power BI.
• Experience designing event-driven and API-first integration architectures using Kafka, REST APIs, GraphQL, or equivalent patterns.
• Strong working knowledge of data modeling, metadata standards (OpenLineage, OpenAPI, DCAT), and enterprise data architecture patterns.

AI & Emerging Technology:

• Familiarity with AI-assisted governance architectures - including how LLMs, RAG pipelines, and agentic frameworks integrate with governance platform ecosystems.
• Experience authoring or reviewing architecture decision records (ADRs) for AI-powered platform features.

Compliance & Security:

• Experience designing governance architectures that support privacy and regulatory compliance (CCPA/CPRA, USGCI, FCC, ISO 27001, ISO 42001).
• Familiarity with data access control patterns, sensitive data classification architecture, and privacy-by-design principles at enterprise scale.

Leadership & Communication:

• Demonstrated ability to influence technical direction across engineering, product, and business stakeholders without direct authority.
• Excellent written and verbal communication skills - able to produce clear architecture documentation, present complex tradeoffs to executive audiences, and facilitate productive design sessions.
• Experience working in agile, cross-functional environments with multiple competing priorities and stakeholders.

Must Have Skills:

• 10+ years of enterprise data architecture or solution architecture experience, with hands-on governance platform expertise.
• Deep knowledge of at least two enterprise governance platforms (Open Metadata, Collibra, Ataccama, Securiti.ai) including integration and extensibility patterns.
• Proven Semantic Layer and/or Metric Catalog architecture experience in production environments.
• Strong integration architecture skills - API design, event-driven patterns, metadata propagation at scale.
• Experience with Databricks, Unity Catalog, Azure, and DBT in large-scale data platform environments.
• Demonstrated experience producing architecture documentation, ADRs, and platform standards adopted by engineering teams.
• Experience architecting for regulatory compliance (CCPA/CPRA, ISO 27001, or equivalent).

Nice to Have:

• Hands-on experience with Open Metadata administration, API extensibility, and custom connector development.
• Experience with dbt Semantic Layer, Cube.dev, AtScale, or similar semantic layer technologies.
• Familiarity with AI agent architecture and LLM integration patterns in governance or data platform contexts.
• Knowledge of OpenLineage, DCAT, or other open metadata standards and their implementation in enterprise catalogs.
• Enterprise architecture certifications: TOGAF, AWS Certified Solutions Architect (Professional), Azure Solutions Architect Expert, or equivalent.
• Experience contributing to open-source data governance projects (Apache Atlas, OpenMetadata, or similar).

TekWissen Group is an equal opportunity employer supporting workforce diversity.