The first step to building a good Data Analytics team is to ascertain your vision for the same. Once you know the kind of roles you will require in your team it will be easier to set up the interview processes.
The big question here is, what is the better recruitment direction- Data Engineer vs Data Analyst? To understand this better, let’s discuss it further. When looking to create the perfect digital team, these are the roles, you can be looking at:
Data Scientist/Analyst role: The job of the data scientist is to put the collected data to use. One of the most popular positions in the feild, with the titles being interchangeable with operations research, research title and so on. There is use of machine learning and artificial intelligence to find insights that are further usable in driving analytics.
Data Engineer role: One of the main roles in a data analytics team, the primary job of the data engineer is to collect data, store it appropriately and manage it in a way that it is made readily available as and when required. They deal with raw data in huge amounts and prepare it in order to help other roles in making feasible business decisions. It wouldn’t be an overstatement to say that it is one of the most pivotal roles in the data analytics chain and there is need for stringent screening to be done in order to recruit the best options available.
Data Translator role: While the above mentioned are established roles in the line of command, there are several new roles that simplify the process of analytics operations. Data translators for instance, are a vital addition acting as a catalyst between regular business operations and data by appropriately manoeuvring the task of insight translation, helping companies making the most of it. They understand algorithms and how it will affect a particular business setting.
Role of a project manager: This role, also commonly known as the product owner assumes responsibility of an appropriate mediator between stakeholders and the analytics team. Explaining what both parties expect from each other and co-coordinating that the same are met is the main function of this role.
Data architect role: The role of a data architect is to manage and streamline data associated with the creation, design as well as deployment of the data architecture of the organization, into sizeable teams that are formed by the engineers over a span of time.
Agile technology use: When work is being done on complex projects, there is use of Agile methodology. It can help in planning and prioritization with projects, adding value to the process. Besides giving the project a definite direction, it can also help in help in appropriate action to be taken on the feedback received by the business from the customers, the end users as well as the stakeholders.
This will lead to increasing the quality of data, and offering effective compliance with different machine learning models and data governance.
While a lot of roles and titles are used interchangeably in the current scenario, it is essential that you ensure what might best suit your set of requirements, to ensure the best results.