Specialise or a generalise? It all depends on how you define these terms.
A SQL Server DBA may be considered to be a specialist by a Enterprise Architect but a generalist by a SSIS expert.
The DBA is currently in great demand and based on predictions re: User Devices and Database Servers , the demand will increase.
The rise of the DBA as a strategic position coincides with the rise of the Supertech . The Supertech is someone who understands at a deep level the performance stack.
I source DBAs regularly for different tasks. Some observations (and they are just observations! ) I’ve made on hiring DBAs and benefits of hiring specialists are:
1) A specialist completes tasks almost instantly. The generalist takes longer.
2) A specialist has learnt before the task. The generalist learns on the job
3) A specialist has written more code – in their speciality
4) A specialist has read more widely on the subject
5) Specialist will tend to procure different jobs to deepen the experience
The specialist benefits by:
1) Generally , higher renumeration \ pay
2) Demand for services increases within the speciality. Expert status
3) Opportunities to become the technical lead
With all these advantages come a few disadvantages for the specialist
1) Are you involved in an in demand technology?
2) Are you dedicating adequate time to in depth learning
3) Are you able to contribute in a hybrid environment?
Benefit of the generalist , based on observations
1) Open to wider technology skills
2) More flexible within an organisation and can adapt to platform integration changes
The disadvantage of the generalist
1) Overlooked as the lead on technical projects
My own experience is a mixture of the above , but certain trends in my work career have emerged. The main principles are:
1) Generalist on a the database platform but certain areas of expertise: performance tuning , capacity planning, HA, troubleshooting
2) Primary skills must be backed up by Secondary skills. SQL Server as primary , DB2 and Oracle as secondary skillsets
3) Aim to develop deep learning on the whole stack , whilst maintaining core expertise on certain areas – such as Database Layer:
Application
DBMS – Data System
DBMS - Access system
DBMS – Storage System
DBMS-Buffer system
OS
Hardware
Storage
