About The Company

EazyML, recognized by Gartner, is a pioneering organization specializing in Responsible AI solutions. Our company is committed to enabling organizations to achieve proactive compliance and sustainable automation through innovative AI-driven technologies. We collaborate with breakthrough startups such as Amelia.ai, positioning ourselves at the forefront of AI innovation and responsible data practices. Our mission is to empower businesses with scalable, ethical, and productive AI solutions that drive operational excellence and foster trust in automation processes.

About The Role

We are seeking a highly skilled and experienced Data Engineer to join our dynamic team on a full-time remote basis. This role is ideal for professionals who thrive on solving complex data challenges and take full ownership of their projects from initial design to final delivery. The successful candidate will be responsible for building and maintaining scalable data pipelines using Microsoft Azure Fabric, leveraging AI to enhance engineering productivity,



and collaborating closely with both technical and business stakeholders to develop data solutions that meet organizational needs.

This position offers the flexibility to work from anywhere within India, providing an excellent opportunity to contribute to cutting-edge AI solutions in a flexible, remote environment. The role demands a proactive, detail-oriented individual who is passionate about data engineering, cloud technologies, and innovative problem-solving approaches.

Qualifications

Minimum of 5+ years of practical experience as a Data Engineer, with a proven track record of delivering enterprise-grade data solutions.
Strong expertise in Microsoft Azure Fabric, Databricks, and Azure data services, with hands-on experience in designing and implementing data pipelines.
Deep understanding of SQL, data modeling concepts, and data architecture best practices.
Experience building robust data integration solutions and mana

📌 Data Engineer (India)
🏢 FetchJobs.co
📍 India