Software Engineer (Typescript) Jobot
Seattle, WA6 days ago
- $180,000–$220,000 Per Year
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Skills
- Access Controlunmatched
- Adverse Eventsunmatched
- Application Programming Interface (API)unmatched
- Architectural Designunmatched
- Architectural Servicesunmatched
- Artificial Intelligence (AI)unmatched
- Artificial Intelligence (AI) Agentsunmatched
- Best Practicesunmatched
- Business Intelligence Softwareunmatched
- Cisco Unityunmatched
- Computer Scienceunmatched
- Cross-Functionalunmatched
- Customer Support/Serviceunmatched
- Data Modelingunmatched
- Data Qualityunmatched
- Design Patterns Programming Methodologiesunmatched
- Diversityunmatched
- Documentationunmatched
- Ecosystemsunmatched
- Enterprise Architectureunmatched
- Enterprise Data Integrationunmatched
- FCC (Federal Communications Commission)unmatched
- GraphQLunmatched
- ISO (International Organization for Standardization)unmatched
- Information Technology & Information Systemsunmatched
- Internet Securityunmatched
- Interoperabilityunmatched
- Leadershipunmatched
- Mentoringunmatched
- Metadataunmatched
- Metricsunmatched
- Microsoft Product Familyunmatched
- Microsoft Windows Azureunmatched
- Multiplatform/Cross-Platformunmatched
- Open Sourceunmatched
- People Managementunmatched
- Performance Metricsunmatched
- Power BIunmatched
- REST (Representational State Transfer)unmatched
- Regulationsunmatched
- Regulatory Complianceunmatched
- Software Engineeringunmatched
- Standards Developmentunmatched
- Strategic Planningunmatched
- Technical Leadershipunmatched
- Technical/Engineering Designunmatched
- Time Managementunmatched
- Vendor/Supplier Selectionunmatched
- Workforce Managementunmatched
Description
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Position: Lead I - Software Engineering
Location: Bellevue WA
Duration: 6 Months
Job Type: Temporary Assignment
Work Type: Onsite
Job Description:
- 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 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.
Technical Leadership & Stakeholder Engagement:
- Serve as the architectural authority and technical escalation point for Data Governance engineering teams - providing guidance on complex integration challenges, platform decisions, and design tradeoffs.
- Facilitate architecture reviews, design sessions, and technical working groups with engineering, data, product, and business stakeholders.
- Produce and maintain comprehensive architecture documentation: platform architecture diagrams, integration maps, data flow diagrams, ADRs, and governance platform standards.
- Mentor senior engineers on architecture principles, integration patterns, and platform engineering best practices.
- Represent the Data Governance architecture perspective in enterprise architecture forums, data council meetings, and cross-functional governance bodies.
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 T-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.
TekWissen Group is an equal opportunity employer supporting workforce diversity.
Numbers & Facts
| Location | Bellevue, WA |
| Industry | Computer/IT Services |
| Salary | $72.38 |
| Company Size | 100 to 499 employees |
| Year Founded | 2009 |
| Website | http://www.tekwissen.com/ |
About Company
WE THE TEKWISSEN PEOPLE
TekWissen offers you a broader portfolio of services, industry-leading solutions, and the meaningful innovations that give you greater flexibility and speed to respond to market dynamics, reduced costs and risk to improve enterprise performance, and increased productivity to enable growth.
To keep pace with global market demands, TekWissen keeps its finger on the pulse of change. Our organized approach to guiding a project from its inception to closure. Managing projects is becoming more and more important as we enter the digital era. To cope with the pace that this transition demands, a method is required to manage projects so they can yield quality work, while incorporating efficient use of time and resources.
Project involves identifying which quality standards are relevant to the project and determining how to satisfy them.
It is important to perform quality planning during the Planning Process and should be done alongside the other project planning processes because changes in the quality will likely require changes in the other planning processes, or the desired product quality may require a detailed risk analysis of an identified problem. It is important to remember that quality should be planned, designed, then built in, not added on after the fact.
Capabilities and accomplishments in one TekWissen business enhance the opportunity for success in the others. Put simply, TekWissen's unique combination of attributes promotes success.Similar Job Searches
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