Remote Hadoop/Kafka data engineering jobs

Hadoop is an open-source software framework for storing and processing data, particularly large datasets, on clusters of commodity hardware in a distributed computing environment. It enables clusters to interpret large datasets quickly by making it easier to distribute the calculations over many computers. Hadoop has become the foundation of managing large data systems, which in turn play a crucial role in numerous Internet applications.

Software written in Java and Scala and marketed as open-source, Apache Kafka is a popular event streaming platform used by developers for data integration, analytics, high-performance data pipelines, and mission-critical applications. Companies have been hiring Kafka developers since the tool has gained immense fame in the last few years.

From giant companies like Netflix, LinkedIn, and Uber to car manufacturers, many of the world’s top organizations rely on Kafka for processing streaming data at a rate of trillions of events per day. The messaging platform was originally built to support a messaging queue by Apache Kafka, an open-source tool licensed under the Apache License. Today, developers are using Kafka to create real-time streaming pipelines and apps that process and analyze data as it arrives.

Hadoop provides businesses with a unique opportunity to target consumers and provide customized experiences to each of them by converting data into actionable content. Businesses that can successfully convert data into actionable content using Hadoop will be in the best position to come up with fantastic advertising, marketing, and other business strategies designed to attract customers.

It is safe to say that Hadoop/Kafka data engineers will continue to be in high demand.

A Hadoop Developer is responsible for developing and programming Hadoop applications. These developers create applications to manage and maintain a company’s big data. They know how to build, operate, and troubleshoot large Hadoop clusters. Therefore, larger companies looking to hire Hadoop developers need to find experienced professionals who can meet the company's needs for building large-scale data storage and processing infrastructure.
Kafka developers are expected to carry out end-to-end implementation and production of various data projects along with designing, developing, and enhancing web applications and performing independent functional and technical analysis for various projects. These developers work in an agile environment where they design a strategic Multi Data Center (MDC) Kafka deployment. In addition to having expertise in various functional programming approaches, working with containers, managing container orchestrators, and deploying cloud-native applications, they should also have experience in Behavior Driven Development and Test Driven Development.
Hadoop/Kafka data engineers generally have the following job responsibilities:

• Develop high-performance, low-latency data analytics applications
• Automate the synchronization and processing of complex data streams using data pipelines
• Develop data processing and data storage components in cooperation with data scientists/engineers, designers, and front-end developers
• Design and build relational database models and integrate comprehensive tests to ensure high-quality products
• Assist documentation team in providing good customer documentation by loading data from disparate datasets
• Contribute to developing analytic data assets and implementing modeled attributes

When you're seeking a Hadoop/Kafka data engineer job, you'll need to consider degrees and eventually the right major. It's not easy to get a Hadoop/Kafka data engineer job with only a high school diploma. The best-positioned candidates for a Hadoop/Kafka data engineer job are those who have earned Bachelor's or Master's degrees.

To excel in your field, it is important that you gain hands-on experience and knowledge. Internships are one way for you to do this. Certification is also important for many reasons. For instance, certification distinguishes you from non-certified Hadoop/Kafka data engineers, allowing you to take pride in your accomplishments and know that you are one of the more highly skilled professionals in your field. Certification also opens up doors for better opportunities that can help you grow professionally and excel in your respective field as a a Hadoop/Kafka data engineer.

Below are some of the most important hard skills a Hadoop/Kafka data engineer needs to succeed in the workplace:

Hadoop/Kafka data engineer jobs require certain skills and basics. So Hadoop/Kafka data engineers must start learning the fundamental skills that can get them high-paying Hadoop/Kafka data engineer jobs. Here is what you need to know!

1. Knowledge of Apache Kafka architecture

To understand the Apache Kafka platform, it is helpful to know about its architecture. Although it sounds complex, the architecture is actually quite straightforward. The Kafka architecture is simple and efficient and offers you the ability to send and receive messages in your applications. This combination of efficiency and usability makes Apache Kafka highly desirable.

2. Kafka APIs

In addition to other recommended skills, a Hadoop/Kafka data engineer must be versed in four Java APIs: the producer API, consumer API, streams API, and connector API. These APIs make Kafka a fully customizable platform for stream processing applications. The streams API offers high-level functionality that allows you to process data streams; using the connectors API allows you to build reusable data import and export connectors.

3. Basics of Hadoop

Becoming prepared for a Hadoop/Kafka data engineer remote job requires a thorough understanding of the technology. A fundamental grasp of Hadoop's capabilities and uses, as well as its benefits and drawbacks, is essential to learn more sophisticated technologies. To learn more about a specific area, refer to resources available to you both online and offline. These can be tutorials, journals and research papers, seminars, and so on.

4. SQL

You will need a solid understanding of Structured Query Language (SQL) to be a Hadoop/Kafka data engineer. Working with other query languages, like HiveQL, will significantly benefit you if you have a strong understanding of SQL. You can further improve your skills by brushing up on database principles, distributed systems, and similar topics in order to broaden your horizons.

5. Hadoop components

After you have learned about the Hadoop principles and what technical abilities are required to work with it, it is time to move on and find out more about the Hadoop ecosystem as a whole. There are four main components of the Hadoop ecosystem.

• Hadoop distributed file system
• Map-reduce
• Yet another resource negotiator
• Hadoop common

Hadoop/Kafka data engineer developers, like athletes, must practice effectively and consistently in order to excel at their craft. As their skills improve, they must also work hard enough to maintain those skills over time. To ensure progress in this area, developers need to follow two key factors: the assistance of someone more experienced and effective in practice techniques while you're practicing. As a Hadoop/Kafka data engineer, you need to know how much to practice and watch out for burnout signs by having someone keep an eye on you!

Turing offers the best remote Hadoop/Kafka data engineers that suit your career trajectories as a Hadoop/Kafka data engineer. Take on challenging technical and business problems on the latest technologies and grow quickly. Join a network of the world's best developers & get full-time, long-term remote Hadoop/Kafka data engineer jobs with better compensation and career growth.

Turing allows its Hadoop/Kafka data engineers to set their own rates. Turing will recommend a salary at which we are confident we can find you a long-term job opportunity. Our recommendations are based on our analysis of market conditions, as well as the demand from our customers.