Data Architect: Azure, Databricks & AI

Numentica

  • San Diego, California
  • 16 days ago

    Highlights

    Location: Onsite at Los Angeles, CA OR Houston TX. We are seeking a Enterprise Data Architect with strong hands-on experience designing and modernizing enterprise-scale data platforms, with a focus on Azure, Databricks, data governance, and AI-ready architectures. Experience designing lakehouse architectures, AI/ML-ready data platforms, semantic layers, and scalable data pipelines .

    Numbers & Facts

    LocationSan Diego, California
    Websitehttp://www.numentica.com

    Description

    Contract to hire: About 3 to 6 months fulltime conversion to our client FTE role.

    Location: Onsite at Los Angeles, CA  OR Houston TX

    We are seeking a Enterprise Data Architect with strong hands-on experience designing and modernizing enterprise-scale data platforms, with a focus on Azure, Databricks, data governance, and AI-ready architectures.

    Key Requirements:

    • 8+ years of experience in Enterprise Data Architecture, Data Engineering, or Data Platform Modernization.

    • Strong hands-on expertise in Azure Databricks, ADLS Gen2, Microsoft Fabric, Synapse, Azure Data Factory, and Spark.

    • Deep understanding of enterprise data modeling, integration, metadata management, data lineage, governance, and security.

    • Experience designing lakehouse architectures, AI/ML-ready data platforms, semantic layers, and scalable data pipelines.

    • Experience with GenAI, vector databases (Pinecone, pgvector, Qdrant), and AI-driven data architectures preferred.

    • Knowledge of enterprise governance tools such as Microsoft Purview, Collibra, Informatica Cloud Data Governance or Alation.

    • Proven ability to lead enterprise architecture strategy while remaining hands-on with technical design and implementation.

    • Strong communication skills and experience collaborating with senior technology and business stakeholders.

    Industry Preference: Financial Services experience preferred, but not mandatory.



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