Senior Data Engineer - Microsoft Fabric (Immediate Joiner)
Why This Role Stands Out
You can advance your career as a Senior Data Engineer with EazyML, a Gartner-recognized leader in Responsible AI, by building scalable data pipelines on Microsoft Azure Fabric and leveraging AI for enhanced productivity in this fully remote role. This position is perfect for an experienced data engineer who thrives on solving complex challenges and collaborating with stakeholders to deliver impactful solutions. Apply now to join a dynamic team and contribute to innovative AI-driven projects.
Quick Overview
Job Description
EazyML, recognized by Gartner, EazyML () 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 Azure 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 Azure 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 Azure 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).
Skills
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