This role is for one of Weekday’s clients
Salary range: Rs 400000 - Rs 1300000 (ie INR 4 - 13 LPA)
Min Experience: 5+ years
Location: Gurgaon, Haryana, India
JobType: full time
We are seeking an experienced Data Engineer with strong expertise in the Azure ecosystem and Microsoft Fabric to design, develop, and optimize modern data engineering solutions. The ideal candidate will have hands-on experience with lakehouse architecture, data pipelines, ETL/ELT processes, and data transformation across diverse data sources.
You will work closely with cross-functional teams to understand data requirements and build scalable, reliable, and cost-effective data solutions using Azure and Microsoft Fabric.
Key Responsibilities
Design, develop, and maintain scalable data engineering solutions using Azure and Microsoft Fabric.
Build and orchestrate data pipelines using Azure Data Factory and Microsoft Fabric Dataflows Gen2.
Develop robust ETL/ELT workflows for ingesting and transforming structured and semi-structured data.
Work with Microsoft Fabric Lakehouse and OneLake to implement modern data lakehouse architectures.
Develop efficient data transformations and integration workflows using SQL, PySpark, and Python.
Optimize data pipelines, workloads, and compute resources to improve performance and control cloud processing costs.
Collaborate with business, analytics, and technology teams to translate data requirements into scalable technical solutions.
Ensure data pipelines are reliable, maintainable, and designed according to modern data engineering best practices.
Troubleshoot data integration and pipeline issues and implement appropriate improvements.
Contribute to the evolution of the organization's Azure and Fabric-based data platform.
Required Qualifications & Skills
5+ years of professional experience in Data Engineering, particularly within the Azure ecosystem.
Strong hands-on experience with Microsoft Fabric, including Lakehouse, Dataflows Gen2, and Data Pipelines.
Profic
📌 Data Engineer (Gurugram)
🏢 Weekday AI
📍 Gurugram
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