Senior Data Engineer
My client is looking fort a Senior Data Engineer.
Responsible for developing and implementing data management processes, including data integration, data migration, and data storage. Responsible for ensuring that data is secure and compliant with relevant regulations, such as GDPR. This may involve implementing data access controls, data encryption, and data masking. Responsible for creating and maintaining ETL (Extract, Transform, Load) processes for structured and unstructured data. Responsible for the technical approach to data integrity and back-out plans for all changes to the systems. Manage the deployment and release of data pipelines and applications. Contribute to the development and execution of the organization's data strategy and roadmap. Responsible for staying up-to-date with industry trends in data management and data engineering, ensuring that the organization is using the latest tools and technologies.
ETL Tools: Experience using ETL tools such as Informatica IICS, with an understanding of how these can complement or transition into Microsoft Fabric's Data Factory pipelines. Azure Cloud Computing: Experience using Azure services such as Azure Managed Instance, Azure Data Lakes, and Azure SQL to build scalable and secure cloud-based data solutions. SQL Coding: Proficient in T-SQL for querying, data manipulation, and performance tuning. MSSQL Stack: Hands-on experience with the Microsoft SQL Server stack, including SSMS, SSIS, SSRS, and SSAS. SQL Server Optimisation: Knowledge and practical experience in SQL Server optimisation techniques, including indexing strategies, query tuning, and execution plan analysis. Database Design: Skilled in designing efficient, scalable, and conformant relational database schemas. SQL Server Troubleshooting: Experience diagnosing and resolving performance and connectivity issues in SQL Server environments. Agile Methodologies: Practical experience working in Agile environments, including Scrum and Kanban frameworks, with a focus on iterative delivery and stakeholder collaboration. Unit Testing: Familiarity with unit testing practices for data pipelines and SQL procedures to ensure reliability and maintainability.