Data Engineers

As a Data Engineer with 5+ years of experience, you have the exciting opportunity to join a leading global AI & Analytics organization that specializes in cutting-edge data solutions and advanced analytics. The company is looking for professionals like you who have strong expertise in Azure Databricks, PySpark, ADF, SQL, and ETL pipelines to build scalable enterprise data solutions. Key Responsibilities: - Design and develop scalable data pipelines using PySpark & Spark SQL on Azure Databricks - Build and orchestrate ETL workflows using Azure Data Factory (ADF) - Develop and maintain Lakehouse architecture using ADLS & Databricks - Perform data cleansing, normalization, deduplication, and transformations - Monitor data pipelines, troubleshoot issues, and ensure smooth production support - Collaborate with BI, Data Science, and DevOps teams on enterprise analytics initiatives Qualifications Required: - 5+ years of experience in Data Engineering - Strong hands-on experience with Azure Databricks, Azure Data Factory, ADLS - Expertise in PySpark, Spark SQL, SQL, ETL Development - Good understanding of data architecture and cloud platforms - Strong communication and stakeholder management skills By joining this organization, you will have the opportunity to work with a leading AI & Analytics brand, gain exposure to enterprise-scale cloud data projects, and be part of a high-growth learning environment with the latest technologies. Immediate to short notice candidates are preferred for this role. As a Data Engineer with 5+ years of experience, you have the exciting opportunity to join a leading global AI & Analytics organization that specializes in cutting-edge data solutions and advanced analytics. The company is looking for professionals like you who have strong expertise in Azure Databricks, PySpark, ADF, SQL, and ETL pipelines to build scalable enterprise data solutions. Key Responsibilities: - Design and develop scalable data pipelines using PySpark & Spark SQL on Azure Databricks - Build and orchestrate ETL workflows using Azure Data Factory (ADF) - Develop and maintain Lakehouse architecture using ADLS & Databricks - Perform data cleansing, normalization, deduplication, and transformations - Monitor data pipelines, troubleshoot issues, and ensure smooth production support - Collaborate with BI, Data Science, and DevOps teams on enterprise analytics initiatives Qualifications Required: - 5+ years of experience in Data Engineering - Strong hands-on experience with Azure Databricks, Azure Data Factory, ADLS - Expertise in PySpark, Spark SQL, SQL, ETL Development - Good understanding of data architecture and cloud platforms - Strong communication and stakeholder management skills By joining this organization, you will have the opportunity to work with a leading AI & Analytics brand, gain exposure to enterprise-scale cloud data projects, and be part of a high-growth learning environment with the latest technologies. Immediate to short notice candidates are preferred for this role.