BUG: datetime64[s] fails round trip using .to_parquet and read_parquet

[noahblakesmith]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

c = pd.Series(["2024-01-01", "2025-01-01", "2026-01-01"], dtype="datetime64[s]")
df0 = c.to_frame()

print(df0.dtypes)
df0.to_parquet("test.parquet")

df1 = pd.read_parquet("test.parquet")
print(df1.dtypes)

Issue Description

The dtype changes from datetime64[s] to datetime64[ms].

Expected Behavior

I would expect the dtype to remain unchanged.

Installed Versions

INSTALLED VERSIONS

---

commit : 0691c5c
python : 3.10.16
python-bits : 64
OS : Linux
OS-release : 6.8.0-1021-azure
Version : #25-Ubuntu SMP Wed Jan 15 20:45:09 UTC 2025
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 2.2.2
pytz : 2025.1
dateutil : 2.9.0.post0
pip : 25.0
Cython : None
sphinx : None
IPython : 8.34.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.3
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.3.0
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : 5.3.1
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 19.0.1
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.39
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlsxwriter : None
zstandard : None
tzdata : 2025.1
qtpy : None
pyqt5

[rhshadrach]

Closing as a duplicate of #60774.