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Nowadays more and more organizations collect, process, and analyze massive amounts of data. Thus the technologies and solutions that enable businesses to gain actionable insights from it coninue to rise. IDC forecasts that worldwide revenues for big data and business analytics will increase to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%.
Big data specialists help companies extract data from a variety of sources, as well as store, manage, and analyze it. Since large companies and enterprises are having a hard time handling their increasing data flow, the demand for big data developers and the cost of their services are growing rapidly. According to Glassdoor, an average salary of a senior big data developer in the US surpasses $123,000 annually. Yet finding qualified specialists for your project proves to be extremely challenging. So which criteria to use when choosing big data developers?
Source: Grey Campus
1. Strong technical expertise
Since big data developer is a technical job, it requires substantial expertise in a wide range of technologies and tools. These professionals should have a solid understanding of physical database design principles and the system development life cycle. Big data developer tech stack spans a myriad of tools, platforms, and software. For instance, deep knowledge of Hadoop ecosystem, Apache Spark, Pig and Hive are a must-know for any professional big data developer as well as SQL and NoSQL databases. Additionally, to remain competitive, they have to invest time in learning such programming languages as Python, R, Scala, Java, or C++. Also, big data enginners need to know how to maintain old MapReduce Java code and rewrite it using a more recent Spark technology.
2. Ability to analyze specific business requirements
One of the fundamental skills of a professional big data developer is the ability to understand business needs of a customer and translate them into IT-specific requirements. In such case, big data specialist applies knowledge of the customer’s functions and processes to develop business case and business requirement documents. He may review customer requirements, recommending technological solutions that can be integrated and deployed in the business environment. Moreover, a big data specialist can document the interrelations of businesses and technologies, outlining dependencies and potential risks. In the end, such specialist may evaluate the cost effectiveness and benefits of recommended solutions or alternative options to enhance customer’s capabilities.
3. Big data cloud solutions
Companies are increasingly taking advantage of cloud-based solutions since they can provide real-time access to information from anywhere in the world at any time. Most importantly, applications in the cloud are easier to maintain and scale leading to considerable infrastructure cost savings. That is why expertise in creating cloud solutions is essential for qualified big data developers. This includes experience in working with AWS as well as the ability to use the advanced tools such as Kinesis stream, Firehouse, Lambda, EMR, Spark.
4. Machine learning and Data mining
Big data developers who can master machine learning technology to build predictive analytic apps such as classification, recommendation, and personalization systems are in high demand on the IT job market. This may include expertise in technologies like Mahout, or more specialized techniques like Neural Networks. Big data developers who are well-versed in these technologies may become a valuable asset for your company.
5. Problem-solving skills
Another criterion for identifying a qualified big data developer is the ability to solve problems effectively. Anticipating and identifying problems as well as developing and implementing practical and timely solutions are essential skills for any qualified data professional. This area of expertise requires problems diagnoses by using different problem-solving tools and techniques. A strong big data developer can proactively anticipate and prevent problems by generating multiple potential scenarios and solutions. An experienced professional makes various recommendations for implementation of corrective or preventive actions for complex issues that are unclear in nature. Furthermore, such specialist may identify potential consequences and anticipate the risk levels.
One of the criteria for choosing a great big data developer is the ability to improve organizational performance through the application of innovative thinking. Such specialist explores numerous potential solutions and evaluates them before accepting. In this way, he maintains a balance between innovation and pragmatism when determining the practical application of new ideas. Being driven by innovation, such big data professional makes a lot of proposals, which results in the development of new products, services, and approaches. Additionally, he or she may determine how these innovations will be deployed to produce a return on investment. This may greatly enhance existing and emerging operations, products and processes within an organization.
7. Statistical and Quantitative Analysis
Big data developers with a background in quantitative reasoning and a degree in mathematics or statistics may bring competitive benefits to your company. Therefore, they should have expertise in statistical tools like R, SAS, Matlab, SPSS, or Stata. Yet finding data experts with quantitative background is not likely to be easy.
To sum up, professional big data developers are mostly valued when they have a strong technical background and great problem solving skills. Furthermore, the knowledge of data analysis and business requirements analysis are essential for developing a clear understanding of the business needs. Specialists with such skill sets may handle diverse sources and huge amounts of raw data seamlessly and provide valuable insights from it. This enables big data engineers to use technical solutions that leverage innovative technologies to drive real benefits for your busniess.