It seems to me you want a table of employees with 3 attribute columns, name, id, and designation. So your data has 2 dimensions, employees vs attributes. You can't do that with a single dictionary.
One way to do what I think you want is this. Start by defining the row structure with attributes.
>>> from collections import namedtuple
>>> Employee = namedtuple('Employee','EmpName,Empid,Designation')
Now build the employee dimension.
>>> employees = []
>>> employees.append(Employee(EmpName="Peter", Empid="456", Designation="Country Head"))
>>> employees.append(Employee(EmpName="Suresh", Empid="585", Designation="Director"))
>>> employees
[Employee(EmpName='Peter', Empid='456', Designation='Country Head'), Employee(EmpName='Suresh', Empid='585', Designation='Director')]
Although this is what I think you want, I have to point out that it is not a very useful data structure for further processing. For example, updates are difficult. Suppose Suresh gets promoted to Managing Director. The only way to update this data structure to reflect that is to search through all the employees to find the one you want to update. Or suppose an employee resigns: ditto.
Employees = {"Peter" : {'Empid':"456", 'Designation':"Country Head"}, "Suresh": {'Empid':"585", 'Designation':"Director"}}?