Infosys Snowflake Developer Interview Questions, Process, and Tips

Snowflake offers a unique architecture that separates storage and compute, providing scalability, flexibility, and cost-effectiveness.

• Snowflake's architecture separates storage and compute, allowing for independent scaling of each component.

• Snowflake uses virtual warehouses to allocate compute resources on-demand, optimizing performance and cost.

• Snowflake's multi-cluster shared data architecture enables seamless collab...read more

Time travel refers to the ability to query historical data in Snowflake, while fail safe refers to the system's ability to maintain data integrity and availability in case of failures.

• Time travel allows users to query data as it existed at a specific point in the past, using the TIMESTAMP parameter in queries.

• Fail safe mechanisms in Snowflake ensure data integrity and availability by automatically handling system failu...read more

Live feed is real-time data while extract is historical data.

• Live feed is data that is constantly updated in real-time.

• Extract is historical data that is extracted at a specific point in time.

• Live feed is commonly used for monitoring real-time events, while extract is used for analysis of past data.

• Examples: Twitter feed is live data, while a monthly sales report is an extract.

Join combines data from two or more tables based on a related column, while data blending combines data from different sources without a direct relationship.

• Join is used to combine data from multiple tables based on a common column.

• Data blending is used to combine data from different sources without a direct relationship.

• Join requires a common column to match records, while data blending does not require a common colum...read more

Seeking new challenges and growth opportunities in a more innovative environment.

• Looking for new challenges and opportunities for growth

• Interested in working in a more innovative environment

• Seeking a better work-life balance

I worked on developing data pipelines for ingesting and processing large volumes of data in Snowflake.

• Designed and implemented ETL processes using Snowflake's features like Snowpipe and tasks.

• Optimized SQL queries for performance and scalability.

• Collaborated with data engineers and analysts to understand requirements and deliver solutions.

• Implemented data quality checks and monitoring processes to ensure data integrity...read more