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Harjai Technologies is seeking an experienced Azure Data Engineer to design, develop, and implement robust data solutions using Microsoft Fabric and Azure Data Factory. You will migrate existing data processes, build scalable data architectures, and ensure data accuracy across all layers.
The ideal candidate will drive Medallion Architecture adoption, implement advanced data transformations, and collaborate with cross‑functional teams to deliver reliable data pipelines.
Harjai Technologies is a global IT staffing and solutions provider with three decades of experience, operating since 1995. We help enterprises design, build, and scale IT projects through Global Capability Center (GCC) setup, end-to-end IT solutions, and Interview-as-a-Service, serving over 200 clients across more than 15 industries including BFSI, pharma, healthcare, manufacturing, and technology. With approximately 1,500 employees and offices in Tampa, Dubai, and Mumbai, we combine deep domain expertise with a fast, reliable delivery model.
Azure Data Engineer
Harjai Technologies is a global IT staffing and solutions provider with three decades of experience, operating since 1995. We help enterprises design, build, and scale IT projects through Global Capability Center (GCC) setup, end-to-end IT solutions, and Interview-as-a-Service, serving over 200 clients across more than 15 industries including BFSI, pharma, healthcare, manufacturing, and technology. With approximately 1,500 employees and offices in Tampa, Dubai, and Mumbai, we combine deep domain expertise with a fast, reliable delivery model.
We are seeking an experienced Azure Data Engineer to design, develop, and implement robust data solutions using Microsoft Fabric and Azure Data Factory. This role is crucial for migrating existing data processes, building scalable data architectures, and ensuring data accuracy across all layers. The ideal candidate will drive the implementation of Medallion Architecture and advanced data transformation logic.
Bangalore- Hybrid (3 days in a month WFO) — HYBRID
FULL_TIME