BUG: Fix inconsistency when constructing a Series with large integers in a int64 masked array

- Refered code from PR#50757 similar issue for non masked ints

Author: parthi-siva

pandas/core/construction.py

@@ -47,6 +47,8 @@
     maybe_promote,
 )
 from pandas.core.dtypes.common import (
+    is_float_dtype,
+    is_integer_dtype,
     is_list_like,
     is_object_dtype,
     is_string_dtype,
@@ -503,11 +505,29 @@ def sanitize_masked_array(data: ma.MaskedArray) -> np.ndarray:
     Convert numpy MaskedArray to ensure mask is softened.
     """
     mask = ma.getmaskarray(data)
+    original = data
+    original_dtype = data.dtype
     if mask.any():
         dtype, fill_value = maybe_promote(data.dtype, np.nan)
         dtype = cast(np.dtype, dtype)
         data = ma.asarray(data.astype(dtype, copy=True))
         data.soften_mask()  # set hardmask False if it was True
+        if not mask.all():
+            idx = np.unravel_index(np.nanargmax(data, axis=None), data.shape)
+            if not mask[idx] and int(data[idx]) != original[idx]:
+                if (
+                    is_integer_dtype(original_dtype)
+                    and is_float_dtype(data.dtype)
+                    and len(data) > 0
+                ):
+                    inferred_type = lib.infer_dtype(original, skipna=True)
+                    if (
+                        inferred_type not in ["floating", "mixed-integer-float"]
+                        and not mask.any()
+                    ):
+                        data = np.array(original, dtype=dtype, copy=False)
+                    else:
+                        data = np.array(original, dtype="object", copy=False)
         data[mask] = fill_value
     else:
         data = data.copy()