Azure Data Engineer

Job not on LinkedIn

October 31

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NextHire

Nexthire is a technology driven recruitment platform that enables companies to hire 2x faster with its advanced algorithms based on years of data.The leadership team has several decades of collective experience working for top product development companies in India. We believe in breaking the conventional ideas that have been rooted in the staffing industry. We provide end to end recruitment solutions and are developing amazing tools that will help shape the future of recruitment industry.Trusted by 100+ brands, MNCs and startups alike, we are creating a hiring experience like never before.

11 - 50 employees

📋 Description

• The role will leverage & enhance existing technologies in the area of Data and analytics Solutions • responsible for developing and supporting IT products and solutions using these technologies • deploying them for business users

🎯 Requirements

• 3 to 6 Years of IT & Azure Data engineering technologies experience • Prior experience in ETL, data pipelines, and data flow techniques using Azure Data Services • Working experience in Python, Py Spark, Azure Data Factory, Azure Data Lake Gen2, Databricks, Azure Synapse, and file formats like JSON & Parquet. • Experience in creating ADF Pipelines to source and process data sets. • Experience in creating Databricks notebooks to cleanse, transform, and enrich data sets. • Development experience in the orchestration of pipelines • Good understanding of SQL, Databases, and data warehouse systems, preferably Teradata • Experience in deployment and monitoring techniques • Working experience with Azure DevOps CI/CD pipelines to deploy Azure resources. • Experience in handling operations/Integration with source repository • Must have good knowledge of Data Warehouse concepts and Data Warehouse modelling. • Working knowledge of SNO, M, S, including resolving incidents, handling Change requests /Service requests, and reporting on metrics to provide insights. • Collaborate with the project team to understand tasks to model tables using data warehouse best practices and develop data pipelines to ensure the efficient delivery of data.

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