The term Big Data is used to describe incredibly vast and complex data sets — so huge that it’s impossible to work on them using standard data engineering operations. Instead, a connection between multiple computers has to be made in order to create a powerful infrastructure able to handle such big datasets.
Big Data is produced by virtually every user/customer of a company. Every click and every interaction with a website or app matters and can be mined, stored, and analyzed using complex Big Data techniques.
Owning such huge datasets gives several significant advantages to your business:
- Ability to carefully review the needs of customers.
- Ability to get to the source of an issue fast.
- More possibilities when it comes to targeted marketing (e.g. issuing coupons based on user’s behavior).
- Faster cyber threat detection.
- More data-driven decision-making.
- Ability to analyze your employees’ work and make it more efficient.
- Improved forecasting.
How to start working effectively with Big Data? You need to hire Big Data developers. They can take care of all the important data engineering processes, including Big Data mining, storing, and transforming it into sets clear for your data scientists/data analysts.
But how to hire Big Data developers who will truly fit your project and deliver great results efficiently? We cover the most important things to remember about below.
The crucial tech stack of Big Data engineers
To get the data you need, Big Data engineers use sophisticated technologies that can only be mastered through continuous work on data engineering projects. We list the most important elements of such a tech stack below — these are all the crucial technical skills you should look for in your candidates when you want to hire Big Data developers.
- Expert knowledge of Java and/or Scala
These two programming languages rule the world of Big Data engineering. Of course, if your candidate knows both, that’s better for you, but most will have a preferred solution. You might also want to hire Big Data developers with experience in Python, Ruby, or C++ as these languages can be used for operations with data as well.
- Experience with Apache Hadoop or Spark
Two most popular environments that help with the distributed processing of huge data sets (Big Data). Hadoop is used with Java, Spark with Scala. However, they should not be considered as competitors — in many instances, using both solutions is highly recommended for the best performance. They can also be complemented by another Apache tool, Apache Kafka. Knowledge of this one should also be considered a priority when you plan to hire Big Data developers.
- Experience with relevant frameworks and libraries
While Hadoop and Spark are a great base for running Big Data operations, their functionality can be broadened by the use of additional frameworks and libraries. Examples include Hive (data warehousing), Ambari (improved Hadoop management), and ZooKeeper (centralization of distributed services).
- Database management expertise
Knowledge of both SQL and noSQL is crucial here — these two technologies complement each other perfectly, providing the best performing database management solution for Big Data.
- Experience with all major types of operations on data
These include concepts relevant to both traditional data engineering as well as those strictly Big Data related. The most important areas to mention are data warehousing (e.g. with Apache Hive, Amazon Redshift), building traditional ETL pipelines, data routing (e.g. with Apache NiFi), as well as cloud data computing (e.g. with AWS, Azure).
Soft skills to remember about
While tech expertise is a must to review when hiring Big Data developers, so are soft skills. A specific set of these will not only guarantee better performance of your new hire but also ensure they can cooperate well with their peers across the company.
The most important soft skills to consider when you want to hire Big Data developers are…
- Approachability
To be open to suggestions from non-data teams on what kind of data can be useful for them.
- Business-oriented approach
To always look for new sources of data that can power up the whole business.
- Amazing multitasking
To swiftly jump between multiple daily tasks as well as sudden, unplanned issues that have to be solved ASAP.
The road to becoming a Big Data engineer
Becoming a highly experienced and respected Big Data engineer takes lots of years of both education and later implementing what one learned into an actual business environment. Many top Big Data experts end up offering Big Data consulting services to various clients instead of working for just one company, as this allows them to earn even higher salaries.
Your aim, therefore, should be to hire Big Data developers who already have experience within the business environment but still prefer working for one company instead of going freelance.
Big Data developers are often graduates in majors like applied maths, statistics, cognitive science, computer science, data science, or business analysis. Such background gives them both a vast understanding of the world of data as well as it’s real-life appliances.
The most important job interview questions to ask when you hire Big Data developers
By running a proper technical interview with your candidate, you are able not only to correctly assess their technical skills but also to review how well they fit your company. As such an interview should be run by someone with real-life experience with Big Data, if you are not such an expert yourself, you should consider asking a professional to assist you. This can be either another Big Data engineer, a software consultant, a data-focused IT project manager, or a freelancer providing professional Big Data consulting services.
To give you a better idea of how such an interview can look, we listed below some of the common questions Big Data engineering candidates are asked.
- What does shuffling in Hadoop MapReduce do?
- How to restart NameNode? In what situation would you do it?
- What's the difference between OLAP and OLTP?What are the differences between SQL and NoSQL? In what situations one is preferred over the other?
- How would you approach transferring 1m+ gigabytes log files into a database
- cache() vs persist() in Spark — what is the difference?
- What are the three core methods of Hadoop Reducer?
- What’s a linked list?
- Relation vs non-relational databases — what are the differences?
- How is HDF different from other distributed file systems?
How to assess the experience of your potential Big Data developer?
With the number of Big Data developers growing, you might end up with a bigger choice of who to hire. This allows you to base your final decision not only on their pure skill but also on how well they fit your business. Consider the two areas of the company fit…
- Industry fit
Try to hire Big Data developers who have previously worked within your industry. Such experience gives them the knowledge of the most valuable sources of data for a company like yours and, therefore, allows them to deliver you amazing results faster.
- Company culture fit
Do not underestimate the importance of the match between your company values and your candidate’s preferences — such a match will make your whole company perform better. Consider areas like the preferred style of management, approach to diverse teams, experience with and attitude toward remote work, and other values that drive your business.
Get the most out of Big Data
By hiring Big Data developers, you open a way for your company to acquire data that can be crucial in making future business decisions. However, to make the most out of this opportunity, you will also need other experts on board. These include data scientists (data analysts), business analysts, and IT project managers.
Ideamotive can supply you with all these experts fast. We run a unique network of top IT talents, from web developers and mobile designers to AI experts and machine learning engineers. We always listen to your unique needs and get you connected only with experts who truly fit your business.
