Tech Lead - Data Engineer (Azure)

MResult • Custom Software Development • Analytics & BI Consulting • Azure Data Factory • 2 months ago
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Salary
≈ $29k – $50k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 8+ years exp

First seen by Alion on Aug 21, 2026.

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MResult

MResult is a data management services firm that specializes in leveraging technology to help a range of businesses by providing software development, business intelligence, IT, and data analytics solutions.
mresult.com • Bengaluru • Mangaluru • Data Engineering & Migration Services • Analytics & BI Consulting • 201-500 employees • Est. 2004
Tech stack of MResult

We're hiring a Tech Lead - Data Engineer (Azure) on Microsoft Fabric, based in Bangalore and Mangalore.

Responsibilities:

  • Design and implement scalable data platforms using Microsoft Fabric.
  • Develop and maintain Data Factory pipelines, Dataflows Gen2 Notebooks, and Lakehouse solutions.
  • Create and optimize Medallion Architecture (bronze, silver, and gold) data models.
  • Develop and manage real-time analytics and event streaming solutions.
  • Implement data governance, security, monitoring, and performance optimization within Fabric.
  • Support Customer Insights implementation and customer profile analytics.
  • Design and implement Salesforce Sales Cloud and Data Cloud integrations with Microsoft Fabric.
  • Develop scalable ingestion frameworks for Salesforce objects and metadata.
  • Create unified customer profiles by consolidating Salesforce, Dynamics 365 and external data sources.
  • Develop AI-enabled data solutions using Microsoft Fabric AI capabilities, Copilot, Azure OpenAI, and Microsoft AI Services.
  • Build AI-driven customer insights, predictive analytics, propensity models, and recommendations.

Requirements:

  • 8+ years of data engineering experience.
  • 5+ years of experience with Microsoft Azure Data Platform technologies.
  • 3+ years of hands-on experience with Microsoft Fabric.
  • Experience integrating Dynamics 365 and Salesforce environments.
  • Experience working with large-scale enterprise datasets (> 100M records preferred).
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