Big Data Developer Job Description

Big Data Developer Job Description, Skills, and Salary

Are you searching for a big data developer job description? Get to know about the duties, responsibilities, qualifications, and skills requirements of a big data developer. Feel free to use our big data developer job description template to produce your own big data developer job description. We also provide you with information about the salary you can earn as a big data developer.

 

Who is a Big Data Developer?

A Big Data Developer is someone who develops the technological tools and frameworks that enable a company to incorporate data analytics into business solutions. Your responsibilities are to design, code, monitor, and test the software and applications used to accomplish your firm’s objectives.

Industry-specific job duties for big data developers differ, but their main objective is to ensure that an organization’s technology infrastructure runs smoothly in support of business objectives. They will also write code for crucial business components, lead technical training sessions, and mentor and support less experienced staff. Big data developers might supervise the technical facets of development initiatives or act as the project team leader. They can also explain the company segment’s services to executive management. Big data developers must ensure that all aspects of their job, including the design, testing, and execution, adhere to all relevant rules. They might look into and find alternatives to guarantee corporate needs. Big data developers can draw on their technical expertise and critical thinking skills to choose the best techniques and standards for measuring success.

Big data applications are coded or programmed by big data developers who are experts in fundamental scripting languages. They work with data that cannot be processed conventionally and does not fit into a single machine. The position resembles software development in ways. Most collaborate closely with Big data engineers and scientists to support an organization’s big data requirements.

Big data developers are required to provide their organizations with various data-related IT services. They typically use Big Data software, which enables developers to handle other duties and regular activities while still interpreting theories, debugging, and optimizing data. They are knowledgeable about stream processing, parallel data processing, and programming and have expertise in moving data to big data platforms. Big data developers must be able to operate independently in teams to complete projects, which necessitates frequent collaboration with others.

Big data developers may work in corporate IT departments, governmental organizations, and software development companies. They usually work full-time, though some work more than 40 hours weekly to meet demands or tackle challenging issues. Most of the time, big data developers stay at offices. However, they occasionally travel to conferences or client meetings. They might undergo background checks and security clearance because they frequently work with private or sensitive data.

 

Big Data Developer Job Description

What is a big data developer job description? A big data developer job description is simply a list of duties and responsibilities of a big data developer in an organization. Below are the big data developer job description examples you can use to develop your resume or write a big data developer job description for your employee. Employers can also use it to sieve out job seekers when choosing candidates for interviews.

Big data developers have various duties and responsibilities they need to handle regularly. There may be slight differences due to different workplaces. The primary duties they do are;

  • Create and implement data stores that permit our high-frequency data to be processed and stored in a scalable manner.
  • Create the framework for a big data platform.
  • Collaborate with senior team members including ETL Architects, Business Analysts, QA, etc to implement the development plan.
  • Customize, manage, and store databases, analytical systems, warehouses, and integration tools.
  • Comfortable with automation, usability, balancing, and performance enhancement.
  • Contribute to technical oversight to ensure that the company’s systems and data warehouses are effective, resilient, and long-lasting.
  • Deliver unit-tested source code that complies with the essential requirements and regulations.
  • Execute and manage operations like writing scripts, calling APIs, scraping websites, and writing SQL queries
  • Keep up with the company’s data pipeline.
  • Have a working knowledge of heterogeneous data replication methodologies.
  • Establish best practices and find the best technological solutions in cooperation with other like-minded team members.
  • Participate actively in technology strategies like design, architecture, and interfaces to address the needs of their client’s business.
  • Set up and make available the data-access tools that all data scientists use.
  • Responsible for creating highly performant and scalable web services for tracking data.
  • Review code, give advice on best practices, and enhance performance.
  • Utilize the most recent Java, Scala, and Design, construct and test a large-scale, unique distributed software system in big data technologies.
  • Work with various data sets, analyze huge data vaults, and find insights.

 

Qualifications

  • High school diploma or GED
  • Bachelor’s in computer science or related course (May not be required by some firms)
  • A solid understanding of object-oriented languages like Java, JavaScript, Node.JS, and others
  • Great knowledge of Hadoop and its modules, which are Pig, Flume, Hive, Impala, Spark, Hbase, and Storm
  • At least one year of experience in a similar role

 

Essential Skills

To start and stand out in this career, you should have relevant skills; imbibed and learned. Some of these skills are:

  • Analytical

Analytical skills are one of the most crucial skills needed to become a competent Big data developer. One needs practical math skills and expertise in big data science to understand complex data. Big Data analytics tools can assist one in developing the analytical abilities necessary to address a problem.

  • Big Data Tools Knowledge

Big data developers use big data technologies to extract and analyze insights from enormous databases. They will need to learn more about the business domain, particularly the data they are working with, to understand the data.

  • Cloud Computing

Most big data teams will choose a cloud setup to store data and guarantee high data availability. Organizations like cloud storage because it is more affordable to store large amounts of data than on-site storage facilities. Many businesses even employ a hybrid cloud architecture, where data can be kept on private or public clouds depending on the needs and organizational policies.

  • Communication

The capacity to present knowledge in a way that others can understand is known as communication. Big data developers frequently collaborate with groups of individuals with varying jobs and responsibilities to ensure everyone is aware of their thoughts and proposals. As a result, they need to be effective communicators. When producing project reports or documentation, they also use written communication.

  • Creativity

The capacity to come up with original ideas and solutions is creativity. Big data developers use this skill when creating algorithms, which are detailed instructions that govern how a machine processes data. They employ creativity when making visualizations with charts that understandably present a lot of data.

  • Data Visualization

Big data developers need to develop their data visualization skills. Data must be present to convey the intended message. Because of this, the ability to visualize things is crucial in this field.

To begin developing data visualization skills, they familiarize themselves with the big data tools and software’s data visualization possibilities. Additionally, it will foster their imagination and creativity, which are valuable traits in the big data industry. For data professionals, the capacity to visualize the data is essential.

  • Data Mining

Professionals with experience in data mining are in high demand. To advance in their careers, one needs to acquire knowledge of and exposure to data mining technologies and techniques. Professionals should learn from reputable data mining technologies like Apache Mahout, Rapid Miner, and many others to gain the most in-demand data mining skills.

  • Hadoop

A software system called Hadoop enables large data applications. This open-source application allows data management and creation for developers. Given that Hadoop is one of the most widely used tools in this industry, big data developers need to be proficient with it. Many businesses, including banking, healthcare, and telecommunication hire people with this talent.

  • Machine learning

It would be wise for aspiring big data developers to master machine learning techniques. It helps them to manage intricate data structures and identify patterns that are too intricate to be efficiently handled by more conventional data analytics methods. They need to have mastered statistical programming techniques to develop in this field.

  • Maths

A solid understanding of mathematics and logical reasoning are also required. The sorting of data kinds, algorithms, and other topics should be recognizable. You need database skills to handle a large number of data. Any big data developer with a solid technical and analytical perspective can advance quite far.

  • NoSQL

NoSQL databases like Couchbase, and MongoDB, are now replacing SQL databases like DB2, Oracle, etc. These distributed NoSQL databases assist in addressing the demands for massive data access and storage. This adds knowledge to Hadoop’s data-crunching skills. Anywhere there are openings, NoSQL experts can find work.

  • Organizational

Big data developers can succeed in their jobs by being well-organized. This skill entails planning and scheduling tasks to guarantee projects are finished on time to meet clients’ expectations. Knowing where to retrieve files and papers also entails keeping track of them.

  • Problem-solving skills

In the world of Big Data, problem-solving skills are valuable. Because it consists primarily of unstructured data, big data is a concern. The best person to work with in this area is interested in finding solutions to challenges. They will be more likely to find a better solution to an issue thanks to their ingenuity. Even more than in other fields, creativity, and problem-solving skills are necessary to succeed as a professional in big data.

  • Quantitative Research

Big data naturally involves quantitative analysis since it is based on mathematics applications, particularly calculus and linear algebra. A big data developer will have an advantage in comprehending the statistics and algorithms necessary to succeed in big data tasks if they have the aptitude and expertise in these fields. They should be knowledgeable about R, IBM SPSS Statistics, and other technologies.

  • Structured Query Language (SQL)

SQL functions as a foundation in this Big Data era. A language focused on data is a structured query language. Knowing SQL will be helpful for programmers working with Big data technologies like NoSQL.

  • Technology Inclined

Big Data specialists should know the many technologies and tools employed by the sector. Big Data tools support the investigation, analysis, and conclusion.

One should also have a solid understanding of the principles of algorithms, data structures, and object-oriented languages to become a big data professional. A specialist in the big data market should be able to do and code statistical and quantitative analyses.

Working with data tools and technologies like Python, Scala, Linux, MatLab, R, SQL, Excel, SPSS, and others, is always preferable. There is a greater need for developers with outstanding programming and statistical knowledge and skills.

 

How to Become a Big Data Developer

Depending on the industry you pick, you need different skills for a job as a big data developer. One of the best paths to becoming one is below.

Get an Education

Firstly, you should have your high school certificate or General Educational Development (GED). After that, you can go to a tertiary institution to acquire a bachelor’s degree to work as a Big Data Developer. You can get the technical expertise to work as a big data developer with a bachelor’s degree in computer science, information technology, statistics, or a closely related discipline. Some firms may prefer a master’s degree in computer science or a closely related field.

Gain Experience

When they begin new employment, big data developers often undergo on-the-job training. This training could run for a few months and involve working as a data analyst or big data developer’s assistant. Learning the particular systems and procedures used by the organization may also be part of the training.

Acquire Skills

While gaining experience, you can take the time to acquire soft and technical skills relevant to your career.

Knowledge of big data server software like Hadoop and database languages like SQL are relevant technical skills for the position.

Some soft skills you can acquire are communication, creativity, etc.

Have Credentials

Just like other data professionals, big data developers also require technical qualifications. These credentials show that an individual is qualified for their position and possesses the necessary theoretical and practical knowledge.

 

Where to Work as a Big Data Developer

In addition to the IT industry, there are many other fields where Big Data Developers are needed. Let’s check out these sectors:

Travel, Retail, Finance, Healthcare, Advertising, Manufacturing, Telecommunications, Health Sciences, Entertainment and the Media, Biological Resources, Transportation and Trade, Government. There are countless industries in which Big data developers could excel.

 

Big Data Developer Salary Scale

Big data developers’ annual wages are as high as $170,500 and as low as $55,000 as of the 14th of August, 2022. However, most earn between $104,000 to $135,000. This report is according to ZipRecruiter. There may be numerous prospects for growth and increased pay, which depend on skill level, region, and years of experience.

According to Talent.com, Big data developers earn an average income of £60,000 yearly in the United Kingdom. Entry-level salary starts at £42,703, more experienced earn up to £85,000.

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