In my previous role, I utilized SSIS to design and implement ETL processes, enabling seamless data integration between various sources. I created packages to extract data from multiple sources, transform it according to business rules, and load it into a centralized data warehouse. This involved handling complex data flows, error handling, and performance optimization to ensure efficient data processing.

I handle data transformation and cleansing by leveraging SSIS's built-in transformation components such as Derived Column, Conditional Split, and Data Conversion. I also use Lookup and Fuzzy Lookup for data matching and merging. Additionally, I implement scripts in C# within the Script Component to perform more complex transformations and validations, ensuring data accuracy and consistency.

To optimize SSIS package performance, I focus on reducing data flow complexity by breaking down large packages into smaller, more manageable tasks. I also use parallel processing where applicable and optimize data source connections. Additionally, I monitor and adjust buffer sizes, use indexes on lookup tables, and ensure proper error handling to avoid bottlenecks.

In one instance, a critical database query was experiencing significant performance degradation. I analyzed the query execution plan, identified the bottlenecks, and implemented indexing strategies to improve query performance. I also restructured the query to reduce unnecessary joins and optimized the database schema, resulting in a significant reduction in query execution time.

I ensure data security and compliance by encrypting sensitive data during transit and storage, using role-based access controls, and adhering to data protection regulations. I also implement logging and auditing mechanisms within SSIS packages to track data access and modifications, ensuring that all data handling processes comply with organizational and regulatory standards.