DataFrameGroupBy.shift Loses TimeZone in datetime64 columns
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import datetime as dt
import pytz

df = pd.DataFrame({'a':[1,1], 'date':[dt.datetime.now(tz=pytz.utc), dt.datetime.now(tz=pytz.utc)]})

df.info()

df.groupby('a').shift(0).info()

```
#### Problem description

Causes loss of timezeone meaning that you cannot subtract, etc.

Type turns to `datetime64[ns]`

This does not happen with `df.shift()`

#### Expected Output
`datetime64[ns, UTC]`

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.3
numpy            : 1.17.2
pytz             : 2019.2
dateutil         : 2.8.0
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.1
IPython          : 7.8.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
