Hadoop Developer vs. Data Engineer: What Are the Differences?
Learn about the two careers and review some of the similarities and differences between them.
Hadoop developers and data engineers are two of the most in-demand jobs in the tech industry. If you’re interested in a career in big data, you may be wondering which of these positions is right for you. In this article, we compare and contrast these two roles, discuss the skills and experience needed for each and provide information on job outlook and salary expectations.
What is a Hadoop Developer?
Hadoop Developers design, implement and maintain Hadoop Distributed File System (HDFS) and MapReduce applications on the Apache Hadoop platform. They work with data in various formats including structured, unstructured and semi-structured data. Hadoop Developers use Java, Pig, Hive, and Sqoop to extract data from various data sources and load it into HDFS. They also use Hadoop Streaming to process data in real-time. Hadoop Developers typically have a bachelor’s degree in computer science or a related field.
What is a Data Engineer?
Data Engineers are responsible for designing, building, and maintaining the systems that collect and store an organization’s data. They work with Data Scientists to understand the data needs of the business and design systems that can efficiently store and process data. Data Engineers also build ETL (extract, transform, load) pipelines to move data from one system to another. They often work with Hadoop and Spark to process big data. Data Engineers need to have strong programming skills and be familiar with various database systems.
Hadoop Developer vs. Data Engineer
Here are the main differences between a Hadoop developer and a data engineer.
Job Duties
Both data engineers and hadoop developers have similar job duties, such as designing, implementing and maintaining databases. However, the specific tasks they perform may differ based on their specialty. For example, a hadoop developer may focus primarily on coding, while a data engineer may concentrate more on technical infrastructure. This means that a hadoop developer may spend more time working with software applications, such as Hadoop, whereas a data engineer may dedicate more time to servers and other hardware components.
Job Requirements
Hadoop developers and data engineers typically need at least a bachelor’s degree in computer science or another related field. However, many employers prefer candidates who have a master’s degree in computer science or a related field. Additionally, Hadoop developers and data engineers should have experience working with big data platforms, such as Hadoop, MapReduce and Hive. They should also be proficient in programming languages, such as Java, Python and SQL.
Work Environment
Hadoop developers work in a variety of environments, depending on the company they work for. They may work in an office setting or remotely from home. Data engineers typically work in data centers and other technical settings where they can access large amounts of computing power. This means that data engineers often work full time during regular business hours.
Skills
Both Hadoop developers and data engineers need to have strong technical skills. Hadoop developers need to be proficient in Java in order to develop MapReduce programs, which are used to process large data sets. Data engineers need to be able to work with a variety of programming languages in order to create scripts that can extract data from multiple sources and load it into a central repository.
Both Hadoop developers and data engineers also need to have strong analytical skills. They need to be able to understand complex data sets and identify patterns and trends. They also need to be able to use their findings to make recommendations about how the data can be used to improve business operations.
Hadoop developers benefit from having experience with the Hadoop platform, as well as with other big data technologies. Data engineers do not necessarily need to have experience with Hadoop, but they should be familiar with other big data platforms, such as Apache Spark and Apache Flink.
Salary
Data engineers earn an average salary of $113,717 per year, while Hadoop developers earn an average salary of $105,317 per year. Both of these salaries may vary depending on the size of the company at which you work, location of your job and the level of experience you have prior to pursuing either position.