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Hire Spark Developer

Spark is an Apache project that is positioned as a fast and versatile data processing platform that helps to store and process increasing amounts of data. The first framework for working with Big Data was Apache Hadoop, implemented based on MapReduce technology. If you need batch processing, you better hire Hadoop developer. However, Spark solves the problem of reanalysis and small feedback loops. Once you hire Spark developer, you may get help with handling multiple requests quickly and with minimal overhead.

In the article, we are going to explore features of Spark development, pros and cons of the framework implementation, skills that a Spark coder should have and ways to hire Spark programmer.

Main Features and Capabilities of Spark Framework

The main difference between the Hadoop and Spark frameworks is the way they access the data. Hadoop saves data to the hard drive at every step of the MapReduce algorithm, and Spark vs Hadoop performs all operations in RAM. Thanks to this, Spark processes data in a stream. While hiring a shopping app developer or seeking ERP implementation consulting could be beneficial for certain aspects of your business, engaging a Spark developer offers unique opportunities in big data processing and analytics, fueling your organization’s data-driven decision-making.

Spark helps simplify unconventional tasks connected with processing large amounts of data, as structured as unstructured, and high computational load. Hire spark engineer, so he can provide seamless integration of complex features – such as machine learning and graphing algorithms.

According to Built With, there are 1300 live websites worldwide that are using the Spark framework. To be more precise, the list of top 5 countries where Spark is popular includes the US, Poland, the UK, Germany, and Australia. Among industries where Spark developer for hire is the most helpful are the gaming industry, e-commerce, and financial sphere. These industries require such a tool as Apache Spark as the amount of Big Data increases enormously and needs appropriate management in real-time. We are going to explain how specifically Spark developers can be beneficial in these industries:

  • E-commerce: real-time transaction information can be transferred to a streaming clustering algorithm. Then the results can even be combined with information from other unstructured data sources – for example, with customer reviews or reviews.
  • Financial sphere: Apache Spark developer can help to detect fraud or use risk analysis for authentication. Thus, collecting huge amounts of old logs and combining them with external data sources we get results.
  • Gaming industry: detecting patterns of game events coming in a solid stream in real-time; thus, we can at once respond to them and make a profit, using player retention, auto-correction of the difficulty level.

Today, Spark is used in wide-known companies, such as Amazon, eBay, Yahoo!, Twitter, TripAdvisor, and NASA. It is worth mentioning that Spark is in the list of most popular and most loved frameworks among professional coders according to the Stack Overflow survey in 2020.

Pros and Cons of Spark Framework Usage

To apply the Apache Spark functionality as useful as possible, you should know both the advantages and disadvantages of this multifunctional Big Data processing tool.

Advantages

  • The speed of work at all framework levels (from SQL queries to graph computing and machine learning). Apache Spark development is much more convenient than the classic map-reduce and somewhat more convenient than tools like Apache Crunch and other tools from the earlier generation.
  • Development in different languages. One of the reasons for its popularity is the support of several development languages ​​(Scala, Java, Python, and R).
  • Real-time data processing. Concerning real-time data processing, Spark has no alternatives. It helps to analyze data in real time, how and when it was collected. In particular, Hadoop could only process existing data.
  • Improved performance. Spark is a modification of MapReduce. Users do not risk such significant characteristics of the predecessor as unlimited horizontal scalability and the ability to recover even after serious system errors. The ecosystem includes the app-centric cloud-based service, which is called Cisco Spark. Cisco Spark development exists through a collaboration suite for teams.
  • Spark libraries. Today, standard Spark libraries are a major part of the Apache open-source project. Spark has evolved into a multi-functional data analysis tool. Spark has libraries for structured data (Spark SQL) and SQL, stream processing  (Spark streaming), machine learning (MLlib), and GraphX graph analytics. Also, there are many others open third-party libraries, ranging from those working with connectors to options for machine learning algorithms and storage systems.

Disadvantages

  • Micro-batch pseudo-stream processing. Spark breaks up a continuous stream of data into a series of micro-packets. Therefore, sometimes delays in the order of a second are possible. This feature of Spark should be considered if the time factor is critical for the Big Data application being designed.
  • Poor UDF performance in PySpark. Apache Spark allows us to develop Big Data applications in 4 languages, providing APIs for them. However, while Java and Scala are strongly typed, then Python and R are dynamic languages. Therefore, when interpreting the code in a user-defined function, data is double-converted between the Spark application and UDF.

Apache Spark Developer: Popularity, Skills and Resume Sample

It is noted that the Big Data market in the whole world will grow by 12.3% to 2027. Accordingly, the popularity of tools for working with it will be increasing. Various companies related to Big Data are constantly looking for people who can effectively use relevant technologies and tools. Apache Spark developers are among the most popular specialists that companies choose for analyzing large volumes of data.

These experts should have such tech skills and qualifications to be on the top in the market:

Relevant background for Spark Apache Spark engineer:

  • Data scientist
  • Spark software engineer
  • Full-stack software developer
  • Software developer
  • Apache Spark data engineer
  • Consultant
  • Big Data engineer

Certified Spark Developer Salary in Diverse Countries

Big Data Specialists are one of the most sought after IT positions worldwide. For example, in the USA the average Spark developer salary is $74,895 per year. Based on our Recruiting Team research over several local job portals Ukrainian Spark programmer earns $36,000. In the UK a Spark coder salary is $60,212, while in Switzerland and Germany it is $102,446 and $69,181 accordingly.

There are several ways of finding Spark programmers, and the choice of one depends on the location and type of a project.

  • In-house Spark engineers. Spark coder in-house is suitable for long-term projects. They can be found both through IT companies and through websites for work searching.
  • Freelance Spark developers. It is preferable to contact freelancers for one-time tasks that are indirectly related to Big Data. Since Spark is applied in complex projects, it is not worth delegating a task to freelance for reasons of process transfer complexity and security.
  • Scaling development teams with dedicated Spark engineers. Transferring projects to teams guarantee high-quality results, as they are hired specifically for the features and requirements of your project. You can find such teams through IT companies or Spark offshore agency.

Building a dedicated development team in Ukraine wins thanks to guarantees of the high-quality results, the full dedication of the team, and easy connection with Spark coders thanks to a convenient time zone.

Hire Spark Programmers at Mobilunity

Many businesses from various industries rely on Mobilunity’s recruiting teams, constant support, and talented programmers including Spark developers. Our company has huge experience providing businesses with fully dedicated development teams. We run the process of recruitment thoroughly that suits the requirements of our clients.

How you may benefit from working with Mobilunity:

  • Experts fully dedicated to your project. You can hire a Spark developer who is entirely committed to your project and meets its needs ideally. Besides, you will have all the needed tools for effective communication with your team to control the development process and make sure all is done in compliance with the set deadlines.
  • Experienced developers. With a wide range of diverse specialists at our disposal, our company is ready to take on part of the project work or individual projects as a whole. A rational approach to the use of company budgets and human resources will help you in a reasonable allocation of time and money. 
  • Favorable time zone. Located in Eastern Europe, our company is a few hours flight from the main European capitals. Therefore, teams can easily synchronize their work schedules. It is easy for Ukrainian developers to meet with their European partners and improve remote collaboration.

If you have a great amount of Big Data to manage, you are welcome to contact Mobilunity specialists and hire Spark engineer to strengthen your development team.

All salaries and prices mentioned within the article are approximate NET numbers based on the research done by our in-house Recruitment Team. Please use these numbers as a guide for comparison purposes only and feel free to use the contact form to inquire on the specific cost of the talent according to your vacancy requirements and chosen model of engagement.

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