In today’s fast growing world of technology, businesses and organizations are using data driven strategies for decision-making. They use structured and unstructured data to enhance their business value, and influence their strategy decisions. Use of data gives organizations the ability to compete. Every organization manages its structured and unstructured data types - referred to as big data - differently.
What is big data?
Big data is the strategy used to manage information, and integrate different types of large new data management alongside traditional data management. What every organization does with the large volumes of data is what matters most in the running of their day-to-day business affairs. Volume, velocity, variety, variability, complexity and value define big data.
Processing and analyzing big data from its raw form is what gives it value for the proper management of products, services and insights. Management of big data changes with advancing technology, and every organization needs to accommodate new shifts to provide better services.
Big data generates millions in income for many organizations all over the globe. Many people are seeking jobs in this field, and there are too many organizations waiting to accommodate big data experts. The field is competitive, and the demand for specialists just as high. If you are a big data specialist and willing to take your career to the next level, you are in luck.
Careers to explore in big data
Big data has a wide range of careers to choose from. For people in the technology world, there is no better place to work than the big data industry. Below are 12 of the best careers to explore.
Data scientists are high-ranking professionals that are highly trained to make innovative discoveries in the world of big data. Many work in startups; many in well-established organizations. Their rich knowledge of navigating through data and making analysis possible is a field very few can take on. They are able to identify rich data sources and join them with other sources with less potential, to come up with clean results which help the business move forward.
Data scientists help decision makers in every organization keep up with the shifting technology landscape, where data never stops flowing and changing. Technical limitations do not bog them down and their duty is to make new discoveries, communicate about them and give advice where necessary. Some of the big companies employing data scientists are Yahoo, Facebook, Google, Hive, Amazon, Microsoft, eBay, Twitter and Walmart. With salaries ranging from $65,000 to well over $100,000, this is one of the most sought after big data jobs.
Data engineers are the people responsible for the creation and maintenance of the analytics infrastructure in an organization. They develop, construct, maintain and test all databases and large-scale processing systems. The data engineers create every data used in modelling acquisition, mining and verification.
Data engineers have a solid command of all the scripting languages, and their main duty is to use their skills to improve data quality. They do this by improving the data analytics systems put in place. Data engineering is a very competitive career that pays well.
Big Data Engineer
Big data engineers evaluate, develop, test and maintain big data solutions within the organization. After the architects design their data, the big data engineers take over to build the designs. They have a lot of experience that enables them to get involved the design of big data solutions.
One of the most important qualities required of a big data engineer is sufficient experience in software engineering, object-oriented designing and coding, and testing patterns. They should also have the ability to use different open source tools. Big data engineers get a salary of between $100,000 and $165,000
Machine Learning Scientist
Machine learning scientists work on and research the development of algorithms used in the adaptive system of an organization. Their job is to build methods used to predict product suggestions, recommendations, product demands and forecasting. They have to possess the ability to explore big data that can automatically extract large-scale machine learning and pattern recognition.
Business Analytics Specialist
The main task of a business analytics specialist is to support an organization’s various development initiatives. They make it easier for the organization to understand business issues by assisting in all testing activities, and in the development of test scripts. They do this by carrying out a lot of research work, making, and developing practical cost-effective solutions to any problems facing the organization.
Data Visualization Developer
Data visualization developers are highly skilled, analytical, big data professionals with profound computing skills. It is the duty of a data visualization developer to liaise with users from other functions and analyze what their requirements are. They also take care of administering all the BI systems to ensure their performance is smooth.
A data architect creates blueprints for the organization’s data management systems. They should be easy to integrate, protect, centralize and also protect all data sources. Data architects have a wide knowledge of big data, data modelling, spreadsheets, ETI and a data driven approach to solving complex problems.
Business Intelligence (BI) Specialist
Business intelligence specialists are responsible for supporting the organization’s wide business intelligence framework. The position of a Business Intelligence specialist requires good implementation and management skills, creative development skills, critical thinking, responsible designing techniques, attention to detail, and effective communication skills. If an organization is overwhelmed and needs help, the BI specialist would advise when it is wise to source for big data experts from freelancers at freelance.com.
Data Analytics Manager
A data analytics manager is responsible for managing a team of analysts and data scientists. They are also responsible for analyzing large quantities of information gathered through a business transactional activity, and for configuring, designing, implementing, and supporting data analysis solutions or BI tools.
Machine Learning Engineer
A machine-learning engineer should be in a good position to generate ideas for data changes in the organization, and improve key metrics with the machines. Machine learning engineers work with other engineers and designers. Together, they prototype and test all new ideas that affect how products and services in the organization behave, especially when machines make those decisions.
A statistician’s job is to collect, analyze and interpret qualitative and quantitive company data with statistical theories and methods. They should have the skills and talents of distributed computing, and be knowledgeable about the most important database systems and cloud tools
Business Intelligence (BI) Engineer
Business intelligence analysts work on data analysis, have great expertise, and experience in setting up reporting tools. They query and maintain data warehouses in the organization. Being hands-on with big data, and taking a data driven approach to solving all complex problems should be among their top skills.
Freelance big data analysts have a niche in the big data market as well. If you are a freelancer, join the number of freelance big data analysts in the market, and develop your big data career either as a full-time analyst, or part-time so you can pursue other interests. Whatever you choose, freelance big data analysts make as much money as their corporate counterparts.
Has the above information been of any help to you? If you need to find out more about the interesting careers in the big data industry, ask whatever you wish and leave any comments here. We will get back to you with all the answers and requests.