Hire deeply-vetted Hadoop developers

The Apache Hadoop software library is a framework that allows for the distributed processing of enormous data sets across clusters of computers using simple programming models. It is designed to scale from single servers to thousands of machines, each offering local computation and storage.

Big Data continues to play a big part in different aspects of today’s digital business world, and it’s still growing. Consequently, Hadoop’s popularity continues to rise, as business professionals increasingly rely on it to handle large quantities of data.

Hiring fresh talent in Hadoop requires testing and reviewing candidates for their technical skills and proficiency. That means a fair amount of software development experience is expected. However, if you're coming from a non-technical background and looking to hire a Hadoop developer, we have an excellent resource for you. Here, we will help you understand what it takes to hire dedicated Hadoop developers to build secure and stable applications.

At a senior level, Hadoop developers should have the following technical skills in their arsenal:

Understanding what Hadoop is and its various components are necessary skills every Hadoop developer should have. Hadoop is an open-source framework of big data solutions, and it is expected that a professional developer should know about the different solutions available in this framework. Apart from these solutions, the candidate should also learn about the technologies related to the framework, how they are all interconnected, and their related functions.

Java is among the most popular programming languages available. It allows for the development of Kafka queues and topics. Java is also used to design and implement MapReduce programs for distributed data processing. As a Hadoop developer, there might be a need to develop Mapper and Reducer programs that meet the unique business requirements. Thus, being proficient at programming with Java is imperative to becoming an expert Hadoop developer.

HDFS is the storage system available in Hadoop. It is widely used and popular among organizations and enterprises because it allows them to store and process extensive data at a meager cost. All the processing frameworks available in Hadoop operate on top of HDFS. This includes the likes of MapReduce and Apache Spark. A good understanding of classes, data members, and methods is mandatory for any Hadoop developer.

One of the top skills as a Hadoop developer is the use of Kafka for real-time streams of data and real-time analysis. Kafka offers excellent replication characteristics and higher throughput. Hence you can use it for tracking service calls or IoT sensor data. It also aids in collecting large amounts of data and is used mainly with in-memory microservices for durability.

With Apache Sqoop, it is now possible to transfer data between the HDFS and relational database servers like Teradata, MySQL, and PostgreSQL. It can import data from relational databases to HDFS and export data from HDFS to relational databases. Sqoop is highly efficient and comes in handy for transferring large amounts of data between Hadoop and external data storage solutions such as data warehouses and relational databases.

Apache Spark is an open-source analytics engine used for large-scale data processing. It offers developers an interface to program complete clusters with implicit fault tolerance and data parallelism. It runs in Hadoop clusters through YARN or through its standalone mode to process data in Cassandra, HDFS, Hive, HBase, or any other Hadoop InputFormat. Spark is necessary because it enables applications to run in Hadoop clusters up to 100 times faster in memory. Without a full grasp of this skill, working with large amounts of data would be quite cumbersome.

As a recruiter, you would always want to hire someone who has a strong competency in developing APIs. GraphX is an Apache Spark API that Hadoop developers use to create graphs and perform graph-parallel computation. It combines the ETL (Extract, Transform and Load) process, iterative graph computation, and exploratory analysis in one solution, making it a highly useful and versatile tool. To use GraphX, Hadoop developers also need to be familiar with Python, Java, and Scala, as it only supports these programming languages.

Apart from these core technical skills, an experienced Hadoop developer should also be competent in writing and testing multiple codes, keeping track of new related technologies, and learning them to create advanced app functionality and features.

Creating a hiring funnel will provide you with numerous benefits, like assisting you in selecting the top skills and identifying a Hadoop developer who will fit into your company's culture.

Whether you're an IT recruiter or a project manager, you know that finding talented developers is critical to the success of any project. But direct interviews can help you filter these prospects. So, here are some sample questions to aid your selection for a new Hadoop developer to work on your latest projects:

Here are some more Hadoop developer interview questions that you can ask to assess a developer’s caliber.

• Explain the various Hadoop daemons and their roles in a Hadoop cluster.
• What are active and passive “NameNodes”?
• What read and write consistency guarantees does HDFS provide?
• What is the MapReduce programming paradigm, and how can it be used to design parallel programs?
• Explain the difference between an “HDFS Block” and an “Input Split”?
• What are the main configuration parameters in a “MapReduce” program?