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Job Description & How to Apply Below
- IT Professional 8+ years of comprehensive experience in the Software Development Life Cycle (SDLC), specializing in Azure stack with a proven track record of leveraging Microsoft Azure/Cloud Services to architect and implement scalable data solutions. Skilled in utilizing SQL Data Warehouse, Azure SQL Server, Snowflake, Azure Data Lake, Azure Blob Storage, Azure Databricks, and Azure Data Factory for efficient data processing, storage, and analytics (power BI)
- Design and implement scalable data pipelines using Azure Data Factory, Azure Databricks, Synapse and Snowflake Analytics.
- Develop data models and optimized data storage solutions using Azure SQL Database, and Azure Data Lake (Blob Storage).
- Experience in Azure fabric frame work (creating lake house, ware houses)
- Experience in working with One lake and delta lake for fabric work spaces.
- Experience in migration of on-premises data warehouse to Snowflake, Azure Synapse Analytics, enhancing data accessibility and reporting capabilities.
- Experience in designing and developing scalable data processing frameworks using Apache Spark, enabling efficient processing and analysis of large datasets in both batch and streaming modes.
- Proficiency in Pyspark, SparkSQL for developing notebooks in Databricks
- Experience in Spark SQL for developing notebooks in synapse.
- Have Worked on Event Hubs for processing streaming data in to Databricks.
- Experience in loading/writing data in to Azure data lake using ADF, Databricks, Synapse Analytics
- Proficiency in writing complex SQL queries and stored procedures. Proficient in optimizing data-base performance, ensuring efficient data retrieval, and implementing robust data manipulation logic.
- Proficiency in creating near real-time data pipelines, Enterprise Data Warehouses (EDW), Data Mart’s, and audit and control frameworks. Skilled in designing and implementing solutions that ensure data integrity, compliance, and efficient reporting.
- Implemented CI/CD pipelines using Azure Dev Ops, including automated build, test, and deploy-ment processes.
- Designed and implemented a comprehensive framework of controls for the data governance team, ensuring data adheres to standards of accuracy, completeness, consistency, and compliance.
- Led the design and development of robust data loading frameworks and products, enabling efficient and reliable data ingestion, transformation, and integration across multiple platform
- IT Professional 8+ years of comprehensive experience in the Software Development Life Cycle (SDLC), specializing in Azure stack with a proven track record of leveraging Microsoft Azure/Cloud Services to architect and implement scalable data solutions. Skilled in utilizing SQL Data Warehouse, Azure SQL Server, Snowflake, Azure Data Lake, Azure Blob Storage, Azure Databricks, and Azure Data Factory for efficient data processing, storage, and analytics (power BI)
- Design and implement scalable data pipelines using Azure Data Factory, Azure Databricks, Synapse and Snowflake Analytics.
- Develop data models and optimized data storage solutions using Azure SQL Database, and Azure Data Lake (Blob Storage).
- Experience in Azure fabric frame work (creating lake house, ware houses)
- Experience in working with One lake and delta lake for fabric work spaces.
- Experience in migration of on-premises data warehouse to Snowflake, Azure Synapse Analytics, enhancing data accessibility and reporting capabilities.
- Experience in designing and developing scalable data processing frameworks using Apache Spark, enabling efficient processing and analysis of large datasets in both batch and streaming modes.
- Proficiency in Pyspark, SparkSQL for developing notebooks in Databricks
- Experience in Spark SQL for developing notebooks in synapse.
- Have Worked on Event Hubs for processing streaming data in to Databricks.
- Experience in loading/writing data in to Azure data lake using ADF, Databricks, Synapse Analytics
- Proficiency in writing complex SQL queries and stored procedures. Proficient in optimizing data-base performance, ensuring efficient data retrieval, and implementing robust data manipulation logic.
- Proficiency in creating near real-time data pipelines,…
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