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Location
Remote (India, ET hours)
Seniority
Senior · 5+ years exp
Employment
Full-Time

First seen by Alion on Nov 4, 2026.

Overview
Company
Impact
Profile match
How has EazyML Helped Customers Deliver Business Objectives. Considered by Gartner as an innovative and leading Transparent ML product – "EazyML provides accurate reasons, accompanying reasons with a confidence score to inform the user of the believability / accuracy of the reason".

EazyML, Recognized by Gartner, EazyML (www.EazyML.com) specializes in Responsible AI. Our solutions facilitate proactive compliance and sustainable automation and The company is associated with breakthrough startups like Amelia.ai.

This is a full-time Remote role for an experienced Data Engineer who enjoys solving complex data problems and takes ownership from design through delivery. You can work from home (anywhere in INDIA, job location is in India).

This role is ideal for someone who can build scalable data pipelines on Microsoft Fabric, leverage AI to improve engineering productivity, and work closely with business and technical stakeholders.

Qualifications:

  • 5+ years of hands-on experience as a Data Engineer.
  • Strong experience with Microsoft Fabric, Databricks and Azure data services.
  • Solid knowledge of SQL and data modeling concepts.
  • Experience building enterprise-grade data pipelines and data integration solutions.
  • Proficiency in Python, Spark, or similar technologies is preferred.
  • Experience working with cloud-based data platforms in production environments.

Key Skills:

  • Design, develop, and maintain scalable data pipelines using Microsoft Fabric.
  • Build reliable ETL/ELT processes for structured and unstructured data.
  • Work with business teams to understand data requirements and translate them into technical solutions.
  • Optimize data processing workflows for performance, scalability, and cost.
  • Apply AI-assisted development tools and modern engineering practices to improve delivery speed and solution quality.
  • Troubleshoot production issues and proactively identify improvements.
  • Collaborate with architects, analysts, and developers throughout the project lifecycle.

  • Owns their work. Take responsibility for quality, timelines, and outcomes without constant follow-up.
  • Thinks beyond the obvious. Actively use AI and automation to solve problems, improve engineering productivity, and deliver better solutions.
  • Communicates proactively. Raise risks early, ask questions when something isn't clear, and keep stakeholders informed.
  • Adapts quickly. Requirements evolve, and you're comfortable adjusting priorities while maintaining delivery commitments.
  • Works collaboratively. Available to engage with global teams and can overlap with the U.S. East Coast during critical discussions (up to 1:00 PM ET, as needed).
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