SNOW-2012666: Lazy import of Pandas in snowpark-python

[sfc-gh-nqi]

1. Which Jira issue is this PR addressing? Make sure that there is an accompanying issue to your PR.

   Fixes SNOW-2012666

• Added thread safe lazy loading utilities in lazy_import_utils.py
• Reduced unnecessary imports and optimize memory usage by loading dependencies only when needed
• Fixed type checking with TYPE_CHECKING to avoid runtime imports

2. Fill out the following pre-review checklist:

   • I am adding a new automated test(s) to verify correctness of my new code
     • If this test skips Local Testing mode, I'm requesting review from @snowflakedb/local-testing
   • I am adding new logging messages
   • I am adding a new telemetry message
   • I am adding new credentials
   • I am adding a new dependency
   • If this is a new feature/behavior, I'm adding the Local Testing parity changes.
   • I acknowledge that I have ensured my changes to be thread-safe. Follow the link for more information: Thread-safe Developer Guidelines
   • If adding any arguments to public Snowpark APIs or creating new public Snowpark APIs, I acknowledge that I have ensured my changes include AST support. Follow the link for more information: AST Support Guidelines

3. Please describe how your code solves the related issue.

   Please write a short description of how your code change solves the related issue.

[sfc-gh-jkew]

How much memory does this save, and under what scenarios?

Ok. I found a slack thread discussing this: https://snowflake.slack.com/archives/C055DUP8G5N/p1683910177158739

It's kind of interesting, but the performance is hard to evaluate because almost everything ultimately depends on pandas and pyarrow. We would have to change the connector as well and then determining what the user impact would be hard.