Yes, using a date parameter to control data volume across DEV, UAT, and PROD environments is a common and sensible approach. It allows you to use the same pipeline logic while limiting the amount of data processed in non-production environments, which speeds up testing and reduces resource usage.

A typical setup might look like this:

• DEV: Process only the last 30 days of data for quick development and debugging.
• UAT: Process the last 6–12 months to validate business logic and performance.
• PROD: Process the full historical dataset or, more commonly, use incremental loading based on the last successful run.

The important part is to keep the date range configurable, not hardcoded. Configuration files, environment variables, or pipeline parameters make it easy to change the processing window without modifying the code.

Some best practices include:

• Store environment-specific date ranges in configuration rather than source code.
• Log the start and end dates used for every execution to simplify troubleshooting.
• Test with representative data in UAT so performance and business rules closely match production.
• If possible, use incremental loading (watermarks or last processed timestamps) instead of repeatedly processing the entire dataset in production.

Overall, this approach improves development speed, keeps your ETL or data pipeline consistent across environments, and reduces the risk of introducing environment-specific logic. As long as the date parameter is managed through configuration and thoroughly tested, it’s a clean and maintainable solution.