Lead engineer/data engineer

1 week ago

Hyderabad, India EverestDX Inc Full time

Everest DX – We are a Digital Platform Services company, headquartered in Stamford. Our Platform/Solution includes Orchestration, Intelligent operations with BOTs’, AI-powered analytics for Enterprise IT. Our vision is to enable Digital Transformation for enterprises to deliver seamless customer experience, business efficiency and actionable insights through an integrated set of futuristic digital technologies. Digital Transformation Services - Specialized in Design, Build, Develop, Integrate, and Manage cloud solutions and modernize Data centers, build a Cloud-native application and migrate existing applications into secure, multi-cloud environments to support digital transformation. Our Digital Platform Services enable organizations to reduce IT resource requirements and improve productivity, in addition to lowering costs and speeding digital transformation. Digital Platform - Cloud Intelligent Management (Ci M) - An Autonomous Hybrid Cloud Management Platform that works across multi-cloud environments. helps enterprise Digital Transformation get most out of the cloud strategy while reducing Cost, Risk and Speed. Azure Data Engineer / Lead Hyderabad (Work from Office)Experience: 8–12 Years We are seeking an experienced Azure Data Engineer / Lead with strong expertise in Azure services, distributed data processing, and team leadership. The ideal candidate will have hands-on experience with Azure Databricks, Azure Data Lake, Azure Data Factory, Py Spark/Spark, and SQL , along with the ability to guide a small team on technical design and delivery. Design, develop, and optimize large-scale data pipelines using Azure Databricks, ADLS, and ADF . Implement and manage distributed data processing solutions using Spark/Py Spark . Write and optimize SQL queries for data extraction, transformation, and analysis. Lead and mentor a small team of data engineers, providing technical guidance and reviewing design solutions. Collaborate with stakeholders to translate business requirements into scalable and efficient data solutions. Ensure data quality, governance, and compliance across data platforms. Support production deployments, troubleshooting, and performance optimization. Strong expertise with Azure Databricks, Azure Data Lake, and Azure Data Factory . Hands-on experience in Spark/Py Spark for distributed data processing. Proficiency in SQL for complex queries and optimization. Solid understanding of Azure cloud platform and its ecosystem. Proven experience in leading and mentoring teams .

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