### Apache Airflow Provider(s)

amazon

### Versions of Apache Airflow Providers

_No response_

### Apache Airflow version

2.3.3

### Operating System

MacOs/Linux

### Deployment

Docker-Compose

### Deployment details

_No response_

### What happened

sql_to_s3.py transfer has top level python code imports considered as Bad Practices:

https://github.com/apache/airflow/blob/be31214dcf14db39b7a5f422ca272cdc13e08268/airflow/providers/amazon/aws/transfers/sql_to_s3.py#L26

According to the [official docs](https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#top-level-python-code):

```python
import numpy as np  # <-- THIS IS A VERY BAD IDEA! DON'T DO THAT!
```

All imports that are not related to DAG structure and creation should be moved to callable functions, such as the `execute` method.

This causes timeout errors while filling the `DagBag`:

```
  File "/opt/airflow/dags/mydag.py", line 6, in <module>
    from airflow.providers.amazon.aws.transfers.sql_to_s3 import SqlToS3Operator
  File "/home/airflow/.local/lib/python3.7/site-packages/airflow/providers/amazon/aws/transfers/sql_to_s3.py", line 25, in <module>
    import pandas as pd
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/__init__.py", line 50, in <module>
    from pandas.core.api import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/api.py", line 48, in <module>
    from pandas.core.groupby import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/groupby/__init__.py", line 1, in <module>
    from pandas.core.groupby.generic import (
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/groupby/generic.py", line 73, in <module>
    from pandas.core.frame import DataFrame
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/frame.py", line 193, in <module>
    from pandas.core.series import Series
  File "/home/airflow/.local/lib/python3.7/site-packages/pandas/core/series.py", line 141, in <module>
    import pandas.plotting
  File "<frozen importlib._bootstrap>", line 983, in _find_and_load
  File "<frozen importlib._bootstrap>", line 967, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 677, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 724, in exec_module
  File "<frozen importlib._bootstrap_external>", line 859, in get_code
  File "<frozen importlib._bootstrap_external>", line 917, in get_data
  File "/home/airflow/.local/lib/python3.7/site-packages/airflow/utils/timeout.py", line 68, in handle_timeout
    raise AirflowTaskTimeout(self.error_message)
airflow.exceptions.AirflowTaskTimeout: DagBag import timeout for /opt/airflow/dags/mydag.py after 30.0s.
Please take a look at these docs to improve your DAG import time:
* https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#top-level-python-code
* https://airflow.apache.org/docs/apache-airflow/2.3.3/best-practices.html#reducing-dag-complexity, PID: 7
```

### What you think should happen instead

_No response_

### How to reproduce

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

)
    template_ext: Sequence[str] = (".sql",)
    template_fields_renderers = {
        "query": "sql",
        "pd_kwargs": "json",
    }
    def __init__(
        self,
        *,
        query: str,
        s3_bucket: str,
        s3_key: str,
        sql_conn_id: str,
        parameters: None | Mapping | Iterable = None,
        replace: bool = False,
        aws_conn_id: str = "aws_default",
        verify: bool | str | None = None,
        file_format: Literal["csv", "json", "parquet"] = "csv",
        pd_kwargs: dict | None = None,
        **kwargs,
    ) -> None:
        super().__init__(**kwargs)
        self.query = query
        self.s3_bucket = s3_bucket
        self.s3_key = s3_key
        self.sql_conn_id = sql_conn_id
        self.aws_conn_id = aws_conn_id
        self.verify = verify
        self.replace = replace
        self.pd_kwargs = pd_kwargs or {}