View Creation and Optimization: Design and develop SQL Views to integrate data from various sources, such as transactional databases, data warehouses, and data lakes. Optimize Views for performance and ensure they meet business requirements.
Data Modeling: Collaborate with data engineers, analysts, and other stakeholders to understand data requirements and structure Views that support business intelligence, analytics, and operational needs.
Data Source Integration: Work with data from multiple sources including relational databases like SQL Server, Oracle, etc., data warehouses, and data lakes (Azure Data Lake).
Query Performance Tuning: Analyze and enhance SQL queries to improve performance, ensuring that Views are efficient, scalable, and align with best practices.
Documentation: Document the structure and logic of Views, including table relationships, transformations, and dependencies, to support maintainability and knowledge sharing.
Data Mapping: Try to establish the source and target data mappings, to ensure the support needed for building Data lineage and to support development of data transformation pipelines.
Data Quality Assurance: Validate data consistency, accuracy, and completeness within Views and troubleshoot issues related to data integrity across sources.
Collaboration: Work closely with data architects, data engineers, ETL developers, BI teams and Business Users to provide data accessibility while adhering to governance and data security policies.