Do you know the skills and steps required to successfully transition to a Big Data career?
If you’re someone who doesn’t belong to the Big Data Industry yet but has a background which may have links to it – you may be thinking about a lucrative and long-term Big Data career.
If you’re aspiring to be a Big Data Engineer or a Team Lead/Tech Lead or even a Project Manager/Architect, there are some key technical skills required by employers in the Big Data Ecosystem. These skills vary for different Big Data Roles.
In this article, we will discuss the technical skills required by employers for different Big Data profiles. We’ll also discuss organisational expectations from different hierarchical levels and steps to make a successful Big Data career transition.
Table of Contents
- Essential Skills
- Here are the essential skills needed for making a successful Big Data career transition:
- Distributed Computing Big Data Environments
- Cloud Data Warehouses
- NoSQL & NewSQL
- Data Integration & Visualisation
- Business Intelligence (BI)
- Big Data Testing
- Organisational Expectations and Hierarchical Responsibilities
- An organisation has different expectations from different levels of the workforce:
- Young Professionals (less than 5 years of overall experience)
- Mid-Career Professionals (5 to 10 years overall experience)
- Senior Professionals (overall experience of more than 10 years)
- Transitioning to Big Data
- The following is a breakdown of the kind of activities practitioners can do in these case studies, according to the experience levels.
- Young Professional (less than 5 years of overall experience)
- Mid Career Professional (5 to 10 years overall experience)
- Senior Professionals (overall experience of more than 10 years)
- What should you look for in a good Big Data Program or Course?
- The following are the 3 key expectations you should have of any course:
- Technical skills:
- Cloud platform:
- Case studies/Projects:
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