Today, to run a business successfully, data is as essential as working capital because when a majority of companies have been transformed digitally, data management has now become a core business function for these smart organisations. Data Engineering is a specialised field that helps businesses in the collection, analysis, management and security of the data, in fact the Big Data. And, only a qualified data engineer can effectively deal with the various challenges of data control and governance such as data mining, data flow, data accuracy, data transformation, data warehousing and system stability. This means, a data engineer must be well equipped and skilled with multiple technologies and analytical tools to meet the requirements of technologically smart companies. As the growth of the organisation depends on the optimal use of Big Data, the demand for data engineers is overwhelmingly high and their career prospects are amazingly bright.
Key Responsibilities That A Data Engineer usually Performs Businesses hire data engineers to enhance product development activities, to improve product and service quality, to analyse consumer behaviour, and to forecast market trends to protect the system from IoT threats. Data engineers prepare a huge reservoir of all the relevant information that help them to perform the said tasks professionally and effectively. They design, construct and execute highly scalable data management systems, build functional algorithms, models and proof of concepts.
They also explore opportunities for new data collection, protection of the old data and the optimal utilisation of the both types of data to achieve organisations goals and objectives. They work in various computer languages, develop codes and embed them in the organisation’s data and unlocking the suspicious messages to avert threats. They must also be quick in responding to the other departments of the organisation, meaning they must have good communication skills, discuss important and sensitive issues with IT managers, data architects, modellers and with other key people in the organisation.
Qualifications & Skills Required Besides a tech-savvy mindset, a bachelor’s degree in computer science, computer engineering, applied mathematics, statistics, physics or a related field from a reputed college or university enable one’s to make an easy entry in the world of Big Data and leverage his/her career as a data engineer. One should also have sound knowledge of database architecture, Hadoop-based technologies such as Hive, Pig and MapReduce, practical knowledge of data mining, data warehousing solutions, MatLab, SAS, C/C++, Java and a good familiarity with NoSQL technologies including Cassandra and MongoDB. Since data engineering is a purely technical field, a vendor-specific certification further increases the weight of one’s profile/resume. So, if you are an ambitious young talent and planning to make a distinct niche, then Think Big – Think Big Data.