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Senior Databricks Architect with MS Fabric + P&C Insurance

ET Data Solutions


Job Location:

New York City, NY - USA

Monthly Salary: Not provided by the employer
Posted: 27 October 2026 (Yesterday)
Application Deadline: 24 January 2027
Vacancies: 1 Vacancy

Job Summary

Mandatory Technologies: MS Fabric Databricks PySPark Azure DevOPS Databricks Genie Agent Bricks & Insurance domain exp is preferred and plus.


Responsibilities:
  • Responsible for designing and implementing secure scalable and highly available cloud-based solutions in MS Fabric
  • Experience in enterprise adoption ensures the integration of modern AI-driven capabilities and aligns architecture with key business outcomes
  • MS Fabric Databricks Architect to lead the design architecture and implementation of enterprise-scale data platforms on Databricks.
  • Experience overall data architecture strategy release planning and platform roadmap while partnering closely with customer stakeholders to accelerate Databricks adoption and modernization initiatives.
  • Strong technical leadership customer-facing communication skills and the ability to drive solutions from strategy through execution.
  • Experience in ImplementingAgent Bricksto enable highquality domainspecific AI agents that automatically refine the performance using enterprise data.
  • Experience in creating Data warehouse data lakes for Reporting AI and Machine Learning
  • Integrate Genie and AIBI tools to enable naturallanguage analytics within Databricks One and the broader AI/BI suites.
  • Integrate Azure Data Lake DevOps pipelines and Databricks workflows to achieve seamless end-to-end automation.
  • Experience with integration of different data sources with Data Warehouse and Data Lake is required
  • Understanding of data modelling and data architecture concepts
  • To be able to clearly articulate pros and cons of various technologies and platforms
  • Define and implement cloud governance and best practices.
  • Identify and implement automation opportunities to increase operational efficiency.