Job
Description
As a Senior Azure Data Engineer with expertise in Databricks, your role will involve independently designing, developing, and optimizing cloud-based data solutions. You will be responsible for working on Azure Databricks pipelines, handling data migration from SAP/SQL Server to Azure cloud environments, and building scalable ETL/ELT processes using PySpark, SQL, Delta Lake, and medallion architecture. Your primary focus will be on development tasks, initially 100%, with later involvement in approximately 60% development projects. **Key Responsibilities:** - Work on Azure Databricks pipelinesenhance, modify, and optimize existing pipelines and develop new ones when required. - Handle data migration from SAP/SQL Server and enterprise databases into Azure cloud environments (Lakehouse, Delta, Synapse). - Configure, manage, and optimize Databricks clusters, compute, workspaces, and resources for performance and cost efficiency. - Build scalable ETL/ELT processes using PySpark, SQL, Delta Lake, and medallion architecture across BronzeSilverGold layers. - Work extensively on Azure Data Factory, orchestration pipelines, triggers, monitoring, and integration with Databricks. - Design and maintain data warehouse & dimensional models (Facts, Dimensions, SCD, Star/Snowflake schema). - Ensure strong data quality, validation, governance, and securityincluding Unity Catalog, RBAC, and Azure platform controls. - Develop solutions independently, involving end-to-end development, not just supportinitially 100% development-focused. **Qualifications Required:** - Proficiency in Azure Databricks (Notebooks, Clusters, Delta Lake, Optimization, Resource Configuration) - Experience with Azure Data Lake / Lakehouse Architecture - Familiarity with Azure Data Factory (Pipelines, Orchestration, Integration, Monitoring) - Strong knowledge of Azure SQL / SQL Server - Skills in PySpark, SQL for transformation and performance tuning - Understanding of Data Warehouse Fundamentals such as Star & Snowflake schema, Fact & Dimension modeling, SCD, Data Marts - Exposure to Azure Cloud Services (Key Vault, Storage, Synapse basics, RBAC, security) - Expertise in ETL/ELT development with experience in end-to-end implementation Please note that the location for this position is Gurugram, with an expected experience of 7-10 years and shift timing from 2-11pm. As a Senior Azure Data Engineer with expertise in Databricks, your role will involve independently designing, developing, and optimizing cloud-based data solutions. You will be responsible for working on Azure Databricks pipelines, handling data migration from SAP/SQL Server to Azure cloud environments, and building scalable ETL/ELT processes using PySpark, SQL, Delta Lake, and medallion architecture. Your primary focus will be on development tasks, initially 100%, with later involvement in approximately 60% development projects. **Key Responsibilities:** - Work on Azure Databricks pipelinesenhance, modify, and optimize existing pipelines and develop new ones when required. - Handle data migration from SAP/SQL Server and enterprise databases into Azure cloud environments (Lakehouse, Delta, Synapse). - Configure, manage, and optimize Databricks clusters, compute, workspaces, and resources for performance and cost efficiency. - Build scalable ETL/ELT processes using PySpark, SQL, Delta Lake, and medallion architecture across BronzeSilverGold layers. - Work extensively on Azure Data Factory, orchestration pipelines, triggers, monitoring, and integration with Databricks. - Design and maintain data warehouse & dimensional models (Facts, Dimensions, SCD, Star/Snowflake schema). - Ensure strong data quality, validation, governance, and securityincluding Unity Catalog, RBAC, and Azure platform controls. - Develop solutions independently, involving end-to-end development, not just supportinitially 100% development-focused. **Qualifications Required:** - Proficiency in Azure Databricks (Notebooks, Clusters, Delta Lake, Optimization, Resource Configuration) - Experience with Azure Data Lake / Lakehouse Architecture - Familiarity with Azure Data Factory (Pipelines, Orchestration, Integration, Monitoring) - Strong knowledge of Azure SQL / SQL Server - Skills in PySpark, SQL for transformation and performance tuning - Understanding of Data Warehouse Fundamentals such as Star & Snowflake schema, Fact & Dimension modeling, SCD, Data Marts - Exposure to Azure Cloud Services (Key Vault, Storage, Synapse basics, RBAC, security) - Expertise in ETL/ELT development with experience in end-to-end implementation Please note that the location for this position is Gurugram, with an expected experience of 7-10 years and shift timing from 2-11pm.