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Senior Databricks Architect with MS Fabric Exp.

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Onsite

Senior Databricks Architect with MS Fabric Exp.

Extend Information Systems Inc.

Senior Databricks Architect with MS Fabric Exp.

Skills

DatabricksData AnalysisMachine LearningAIPySparkAzure

2 days ago

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Important information


Contract type:

Freelance / Contract

Location:

New York, NY, USA

Work mode:

Onsite

Published on:

22 October 2026

What they need


Title: Senior Databricks Architect with MS Fabric + P&C Insurance is preferred

Location: NYC, NY- Hybrid 03 day per week

Job Description:

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 Implementing Agent Bricks to enable high‑quality, domain‑specific 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 AI‑BI tools to enable natural‑language 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.

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