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Microsoft Azure Fabric - Tech Lead US

ExusiaUnited States🇺🇸United StatesPosted 14 Aug 2026

Quick Overview

Work Type
Remote
Level
Mid Senior

Job Description

About The Position

Tech Leads - Azure / Microsoft Fabric

Department: Sales and Delivery Team - Empower

Industry: Information Technology & Services, Computer Software, Management Consulting

Location: WFH/ United States Remote

Experience Range: 8 - 15 years

Basic Qualification: Bachelor of Engineering or Equivalent

Travel Requirements: Not required

Website:

Exusia, a cutting-edge digital transformation consultancy, and is looking for top talent in Data Engineering space with specific skills in Azure / Microsoft Fabric to join our global delivery team's Data Engineering practice in India.

What's the Role?

Full-time job to work with Exusia's clients to design, develop and maintain large scale data engineering solutions. The right candidates will also get a chance to work across the entire data landscape apart from data engineering including Data Governance & Reporting & Visualization. The role will provide an opportunity to work closely with client stakeholders to capture the requirements, design and implement end to end data analytics solutions.

Criteria for the Role!

Have a minimum of 8 years' experience in Data management, Data engineering & Data governance space

At least 5 years in a hands-on role using Azure services relevant to data engineering & Analytics and worked on at least 1 project on Microsoft Fabric

Should have worked on large data initiatives and should have exposure to cloud hosted DWH & Data lakes

Education Qualification - Bachelor of Science (preferably in Computer and Information Sciences or Business Information Technology) or an Engineering degree in the above areas

Requirements

Key Responsibilities:

Work with business stakeholders to gather and analyze business requirements, building a solid understanding of the Data Analytics and Data Governance domain

Document, discuss and resolve business, data and reporting issues within the team, across functional teams, and with business stakeholders
  • Should be able to work independently and come up with solution design
  • Build optimized data processing solutions using the given toolset
  • Provide hands on technical leadership and work on multiple projects if required
  • Design pipelines to ingest & integrate structured/semi structured and unstructured data from heterogeneous sources
  • Collaborate with delivery leadership to deliver projects on time adhering to the quality standards
  • Contribute to talent recruitment, competency building and providing mentor-ship to junior resources for these skills

Mandatory Skills:
  • Strong DWH and ETL conceptual knowledge
  • Experience using various components of Microsoft Fabric for storage, Data ingestion and processing, Data governance & reporting
  • Design data solutions and data models using Onelake to support DWH, Data Lake and Lakehouse architecture
  • Data ingestion for batch & streaming data using Data Factory/ Fabric & Databricks
  • Orchestration of data ingestion pipelines using Data Factory or other Azure services
  • Hands on experience using Azure purview for governing data assets including Metadata, Data Catalog & Data lineage
  • Hands on experience using Azure SQL Database, Azure Analysis Services and Synapse Analytics
  • Specific exposure to Microsoft accelerators such as
  • Microsoft Fabric Toolbox
  • Metadata-Driven Ingestion & Processing
  • Experience working with multiple source databases
  • Data migration experience from legacy databases or other cloud ecosystems to Microsoft Fabric
  • Experience is Spark / Pyspark with some hands on with Databricks is highly desired

Nice-to-Have Skills

Provisioning and managing Fabric environment

Knowledge of any other relevant Azure data engineering services

Building and managing PowerBI models on top of Fabric

Exposure to building low code / No code data centric apps using Power Apps

Integrate Power Platform components with Azure based services

Skills

SQL
ETL
Azure
Databricks

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