These days, Big Data is such a large part of the business that there is a high demand for jobs to deal with it at all stages – sorting, analyzing, managing, storing. So, how do you find the best fit for your company?
Here are a few questions that will help you make the best decision for your business.
Qualities of a Good Big Data Engineer
- A keen eye for monitoring data performance
- Ability to modify and adapt infrastructure as needed
- Talent in communication and teamwork as they must work closely with the engineering team to integrate work into production systems
- Knowledge of data processes
- Skilled at Big Data frameworks and Hadoop
- Knowledge of database architecture and design
- Cross-divisional know-how
- Knowledge of data models and data schema
- Programming skills and SQL-based technologies
The world of Big Data is also changing and evolving, so a good Big Data engineer will be flexible and open to learning and feedback, and suggestions if their methods are not working for the business.
Top Interview Questions for a Big Data Engineer
The best way to tell if the person you’re interviewing is right for the job is by asking the right questions. A good Big Data Engineer will have the knowledge and education, but you have to decide what experience level is necessary for your business.
1. Explain Big Data Engineering and why it’s important.
This question helps to weed out who knows their stuff from who doesn’t very early on. Their answers needn’t be creative, but they must be very clear on why it’s important for a business, and perhaps even specifically your business.
2. Specific knowledge-based questions such as What are the various types of design schema in Data Modelling?
They are ‘star schema’ and ‘snowflake schema.’ A basic question that any Big Data engineer should know. Other examples include: explain the components of a Hadoop application, distinguishing between structured and unstructured data, what are the five Vs. of Big Data, and what is a NameNode?
3. How would you work closely with the engineering team to integrate work into production systems?
They might not have the perfect answer, but they should know how to communicate with the engineering team to produce the result that the business needs. If they have no idea, they might not be a good fit for you.
4. Do you prefer good data or good models? Why?
The candidate should answer from experience, but their answer should never really be ‘both’ as it is nearly impossible to have both in real life. If a company has a data model, good data is best-suited, but you can also choose a model based on good data.
5. Will you optimize algorithms or code to make them run faster?
The answer should always be yes. It should depend on the data or model used in the project because real-world performance matters. The candidate’s past projects matter greatly here, whether experienced or inexperienced.
6. How would you transform unstructured data into structured data?
This question may start to be answered with a definition, and the ideal answer contains the candidate’s practical experience as it signals understanding and capability.
7. What are the main responsibilities of a Big Data engineer?
Big Data Engineers manage the source system of data, simplify complex data structure, prevent data reduplication and sometimes provide ELT and data transformation. Any other responses are up to you to decide the relevancy of.
8. Do you have any questions?
The candidate may have some questions for you, and they can often be very telling of the candidate. If they have any, their questions will tell you how eager they are, their motivations, what they know about your business, and what they offer to your team.
Find your Perfect Big Data Engineer Today
You can ask a few interview questions to find a Big Data engineer that’s a great fit, but the results will be worth the time you spend doing multiple interviews.
While doing so, remember that your business intelligence needs can be helped greatly by another type of great fit – business intelligence software. Consider checking out DashboardFox, a self-service BI tool!
DashboardFox is self-hosted and on-premise, meaning that your data will be safe. Data is very important in every industry, and Big Data engineers must always ensure that the data they have in their possession won’t be seen by anyone else that easily.
DashboardFox allows you to set limits as to who can view and access your important data and how much data they can view and access to avoid exposing important bits such as the customers’ personal information and more. It also allows you to control who gets to download data to not get into the wrong hands outside the company.
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Spend more of your precious cash flow on your team, not your software.
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