Sr. DataHub Architect

  • Torrance, CA
  • Posted 21 days ago | Updated 6 hours ago

Overview

On Site
$80 - $84
Contract - W2
Contract - 12 Month(s)

Skills

Analytics
Apache Kafka
Business Intelligence
Collaboration
Customization
Data Governance
Data Quality
Data Security
Data Warehouse
DevOps
Development Testing
Git
Lifecycle Management
Management
Meta-data Management
Metadata Modeling
Microsoft Power BI
Python
Regulatory Compliance
Snow Flake Schema
Storage
Tableau
UI
Unstructured Data
User Experience
Amazon Web Services
Agile
Analytical Skill
Artificial Intelligence
Cloud Computing
Communication
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Analysis
Data Architecture
Data Engineering
Finance
HIPAA
Microsoft Azure
Stacks Blockchain
Leadership
SQL
JSON

Job Details

Senior DataHub Achitect
Location: 
Torrance, CA (Hybrid of 4 days/week onsite and 1 day/week remote)
Contract Duration – July 2025 – March 31, 2026 with possibility of an extension  

We are looking for a highly experienced and strategic Senior DataHub Architect to lead the design, implementation, and governance of our enterprise metadata and data discovery platform. This role is instrumental in shaping our client’s data governance and cataloging strategy, leveraging DataHub as the core platform for centralized data, metadata management, lineage tracking, and data observability.

The ideal candidate will combine deep technical expertise with strategic vision and be comfortable working independently while also leading cross-functional teams across architecture, engineering, analytics, applications, and governance functions.
Key Responsibilities Will Include the Following:

  •  Architect the deployment and customization of DataHub, including storage, ingestion pipelines, and UI/UX extensions.
  • Integrate DataHub with a wide range of systems — data warehouses, lakes, BI tools, data pipelines (e.g. Airflow), and third-party APIs.
  • Extend and customize DataHub metadata models and schema registries as needed.
  •  Design lineage tracking and policy-driven metadata enrichment for structured and unstructured data assets.
  • Work independently with minimal oversight while guiding development and architecture teams toward delivery excellence.
  • Partner with data governance teams to ensure DataHub integration supports metadata harvesting, lineage tracking, and data discovery across platforms.
  •  Build ingestion pipelines using Kafka, REST APIs, Python, and plug-ins to ingest metadata from tools like Snowflake, Power BI, Git, Tableau, etc.
  • Implement best practices for metadata lifecycle management, data quality monitoring, and catalog usage.
  • Work with security and compliance teams to ensure DataHub supports data protection, classification, and auditability.
  • Define and monitor key success metrics for catalog adoption, completeness, and trustworthiness.
  • Collaborate with integration architects to link DataHub with broader IT ecosystems (APIs, DevOps, security, CMS/microsites).
  • Guide data producers and consumers on how to tag, publish, and consume metadata effectively.
  • Guide teams through the delivery lifecycle: design, development, testing, deployment, and monitoring.
  • Review and approve technical designs, solution blueprints, and integration code for quality and alignment.
  • Collaborate with data and platform engineering teams to enable metadata-driven integration and discoverability using DataHub.
  • Manage relationships with vendor partners to ensure alignment with architectural standards and business goals.
  • Establish and maintain governance frameworks for team and vendor partners to ensure the effectiveness of architecture services.
  • Prepare and present weekly and monthly reports on architectural progress, challenges, and achievements.

Will be Working with the following Technologies and Platforms:

  • Cloud (AWS, Azure etc.)
  • Enterprise architecture
  • Software development
  • Infrastructure
  • Databases
  • DevOps practices
  • Microservices and containerization
  • Security and compliance
  • Data analytics and AI/ML
  • Mobile and web applications
  • Salesforce
  • Automotive
  • Captive Finance

Required Skills and Expertise:

  • Bachelor’s or Master’s Degree in Computer Science, Information Systems, Data Engineering, or related field.
  • 8+ years of experience in data engineering, data architecture, or metadata management.
  • 3+ years of hands-on experience implementing and customizing DataHub, preferably in a complex enterprise environment.
  • Strong expertise in the following areas:
    • Metadata standards and lineage frameworks
    • Kafka, REST APIs, Python, SQL, and JSON-based data models
    • Integration with modern data stacks (e.g., Snowflake, Airflow, Git)
  • Experience with CI/CD pipelines, containerization, orchestration, and cloud-native deployments (AWS, Azure, etc.).
  • Extensive experience across multiple domains and technologies.
  • Strong understanding of architectural principles and best practices.
  • Excellent leadership, communication, and interpersonal skills.
  • Proven ability to drive innovation and adopt new technologies.
  • Strong analytical and problem-solving skills.
  • Experience with containerization and orchestration.
  • Understanding of data privacy and compliance frameworks (GDPR, HIPAA, CCPA).
  • Experience in organizations with federated data ownership and large-scale data mesh or data fabric architecture.
  • Background in highly regulated environments

Desired Skills and Expertise:

  • Experience in captive finance, and data analytics sectors is preferred
  • Experience with agile methodologies and DevOps practices is a plus.
  • Familiarity with other metadata is a plus.
  • Relevant certifications are highly desirable.

Should Exude the Following Key Competencies:

  • Strategic Thinking: Develop and implement long-term technology strategies.
  • Leadership: Lead, mentor, and inspire a large team of architects.
  • Communication: Convey complex technical concepts to non-technical stakeholders. Ability to bridge business requirements with technical execution.
  • Innovation: Drive innovation and adopt new technologies.
  • Collaboration: Work effectively with cross-functional teams.
  • Problem-Solving: Address complex technical challenges.
  • Self-motivated and Accountable: thrives in fast-paced, high-autonomy environments.

 

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