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4-5 years of experience in SQL Server database development and data warehouse design. Modernize our data warehouse to ensure reliable, consistent data access. Ensure the stability and performance of SQL Server environments (including SSIS/SSRS/MDS.
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In addition, the candidate should also have some hands-on experience working with the Azure platform and primarily: Azure Data Warehouse / Synapse, Azure Data Factory, Azure Data Lake, Databricks and Azure Analysis Services.
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Knowledge and experience with data warehouse design, dimensional modeling, and data mining. Design, develop, automate, and support complex processes to extract, transform and load data into SQL Data Store and Data Warehouse environments using Visual Studio.
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Minimum 8 years of designing and implementing an operational production grade large-scale data solution on Microsoft Azure Snowflake Data Warehouse. Strong understanding on Azure Architecture, design, implementation and operationalization of large-scale data and analytics solutions on Snowflake Cloud Data Warehouse.
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Work with internal business partners to support efforts to build and activate data warehouse assets and business intelligence tools. Create and manage automated recurring tasks to support dataflow requirements across systems using tools including Mulesoft, SSIS packages, and API integrations.
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Troubleshoot and tune existing Data Warehouse, Dashboards and Reporting systems. Operational Data Warehouse experience. Experience with Microsoft SQL Server 2008 onwards, Transact-SQL, and Business Intelligence Development Studio (SSAS, SSIS, SSRS, Visual Studio.
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Designing and developing SSIS / SQL ETL solutions to acquire and prepare data from numerous upstream systems for processing by QRM. Debug and tune SSIS or other ETL processes to ensure accurate and efficient movement of data.
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Utilize modern database modeling technologies, database tools within a Azure cloud-based database and data warehouse production and development environment. Senior level experience with MSSQL development including stored procedures, SSMS, SSIS, MS SQL Data Modeling tools.
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Extracting, transforming, and loading (ETL) data from various sources into the data warehouse using tools like Informatica, Talend, or SSIS. Data Warehouse and Data Governance Supervisor will, Set standards for database operations, programming, query processes, and security.
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Create complex activities and pipelines in Azure Data Factory for historical and incremental data loads into Microsoft Azure cloud data warehouse and monitor Azure Data Lakes.
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This individual will be responsible for defining high volume data processing pipelines in a multi-tenant environment, verifying data integrity and curating data for consumption by data warehouse, third-party data analytics tools and machine learning models.
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5+ years of experience with Microsoft Big Data solutions with experience in SQL Server (2017 or higher), Azure SQL technologies (Azure Data Lake Gen2, Azure Databricks, Azure Databricks Unity Catalog, Databricks API, Databricks Row-level security, Databricks error logging, Azure SQL Server, and Azure Analysis Services), and a broad experience with related tools (CDC, Columnstore Index, In-memory Table, SSAS Tabular, DAX, T-SQL, SSIS.
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Candidates should have a solid understanding of Data Warehouse architecture and key concepts and working hands-on gathering requirements, assisting with design, data transformation, development, testing and implementation.
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Implementing data quality and data governance processes to ensure accuracy, consistency, and integrity of data in the warehouse. Participating in data warehouse architecture design and providing input on technology selection and best practices.
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SQL Server Mastery: Demonstrated proficiency working with Microsoft SQL Server, encompassing SSIS, SSRS, and advanced data warehousing techniques. Data Warehousing: Demonstrable experience in designing, implementing, and maintaining data warehouses using Microsoft SQL Server, with a keen understanding of best practices in warehouse design.
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