# Choose the ideal data professional for your company > Data engineer, analyst, scientist, or analytics engineer, each solves different problems. How to identify which one to hire for your team. Source: https://www.erathos.com/en/blog/ideal-data-professional-for-your-company Em português: https://www.erathos.com/blog/ideal-data-professional-for-your-company Published: 2022-11-09 Category: Data-Driven Culture ![Data roles comparison: engineer, analyst, scientist, and analytics engineer](https://cms-media.erathos.com/NABpuQbyKjLmFCULV0sWo5RpQ-1.png) So you want to have a data-driven company, right?! 😉 This means you've probably already researched the [advantages](https://erathos.com/blog/a-sua-empresa-e-data-driven/) of launching a data operation, understood the core infrastructures that need to be [implemented](https://erathos.com/blog/data-analytics-3-passos-para-iniciar-a-jornada-data-driven-da-sua-startup-com-ou-sem-time-de-dados/), know how to build your Modern Data Stack, and want to start immediately… But how do you choose the ideal data professional to leverage your strategy? In this blog, we'll explain the key data roles and how each one can help at every stage of your data maturity. ## What is your company's data maturity? What if we told you that every company is somewhere on its data-driven journey, even if they don't know it yet? That's why it's important to understand your company's data maturity. There are a few ways to assess this: ### What results is your organization looking to achieve using your data? First and foremost, you need to kick off any strategic operation in your company with solid planning. After all, how can you know who to hire and where to implement changes without a complete overview of the current state and a clear vision of where you want to go? At this stage, you need to combine a well-defined assessment of what is happening with the knowledge of what needs to be implemented. Therefore, company leadership must be aligned with whoever will lead the data strategy, creating a detailed project plan. But you don't have to walk this journey alone! If you are starting this project from scratch, your company can rely on the help of [strategic partners](https://erathos.com/blog/business-intelligence-como-um-servico-blass-e-pra-voce/), or a data engineering and BI team, who will point out the best implementations for your current stage. ## Data Professionals At each stage of your company's data maturity, it is crucial to have the right professionals on your team. That's why we'll explain what each of them does and how they can help your company advance in its data-driven journey according to each maturity phase. To help you understand the different phases of your company's data maturity, Erathos has developed its own framework to identify which stage your business is currently in: ### 1) Understand your past with Data Engineering and BI In this first stage of the data-driven journey, the goal is to find a way to make your data analysis-ready, available when needed, and quickly updated. In other words: unifying your data sources, moving them to an [analytical model](https://erathos.com/blog/o-que-e-um-banco-de-dados-analitico/), which helps prevent information from being isolated in different departments and systems, meaning, avoiding the so-called [data silos](https://www.youtube.com/watch?v=j6G-Go_LQdI). By implementing the necessary infrastructure to process already collected data, you can get a clear perspective of everything that has been done in the company, build dashboards with historical series, and track metric trends over time. Other critical points to work on in this stage are your company's data literacy and implementing ways to improve the data culture across all departments, bringing your employees into the strategy. ### 2) Monitor your present using Analytics and BI When your company has a solid data, BI, and Analytics infrastructure in place, it becomes much easier to analyze past scenarios and have the necessary arguments to understand and act when something goes off track, or identify new opportunities based on what has already been implemented, opening up room for even more innovation. Once you open up access to data and unlock opportunities with your data infrastructure, it becomes much easier to implement your Analytics and BI framework to get this clearer picture, using ad-hoc analysis, statistical methods, and more robust analysis like RFM and MBA (Market Basket Analysis), establishing realistic long-term goals, and reinforcing outcomes. At this stage, your company has already moved past the basic implementation phase, can perform more robust analysis, and is ready to think about automating certain tasks. When the organization is ready to implement more specialized computing technologies, it means it is entering the third phase. ### 3) Predict your future using Artificial Intelligence The dream of many entrepreneurs when they think about launching a data strategy is to have this process become increasingly modern, automated, and powered by artificial intelligence, machine learning, and deep learning at various levels. However, this doesn't happen overnight. When your company is ready to implement AI-based technologies, it means you are highly advanced in your data maturity, and at this stage, you need the right professionals to run them. Through the data analysis that happens in the company's other stages, it is possible to understand what the problems are, which scenarios repeat most frequently, and where the optimization opportunities lie, in order to minimize errors through automation and artificial intelligence implementations. #### Important notes on data maturity Although we have structured data maturity into a framework, it is important to keep in mind that this is not a linear process. For example, a company might work on multiple fronts simultaneously, such as certain departments that are already highly data-driven, or a data infrastructure that is already scalable, allowing them to apply BI and AI in a short period of time… This varies from organization to organization and can be measured in many different ways. Only a careful assessment of your company's data maturity can outline what is needed to advance through each of these stages. Therefore, it is important to have great BI, Analytics, Engineering, and Data Science professionals close by to help at every stage. ### Data Engineer Within companies, the data engineer is the professional primarily responsible for collecting and processing data, formatting it into a standard that is appropriate for use across all areas of the organization and within an analytical database. They are also responsible for the data pipeline ingestion and update mechanisms. This is the professional who will extract raw data and model it in a usable way so that data analysts and data scientists can generate smarter reports and insights for your company's stakeholders without wasting time collecting and cleaning information. ### Data Analyst These professionals are responsible for analyzing data and information to solve problems within the organization: whether by implementing new frameworks, helping formulate new strategies, or translating data into formats that are easily understood by all stakeholders within an organization. It is the Analyst who will build and analyze the famous Dashboards in BI tools and provide comprehensive reports on the company's status. ### Data Scientist Throughout the process of implementing a data strategy, this professional is key to identifying problems and opportunities stemming from data analysis, understanding and determining key variables and datasets, collecting structured and unstructured data, cleaning and validating databases to ensure efficiency, auditing data, and identifying patterns and trends within the available dataset. With a data scientist on board, you can reach crucial conclusions and pinpoint opportunities to guide decision-making. ## Conclusion For every stage of your data-driven journey, there is a data professional who can help your company reach even higher ground and revolutionize your strategy. Every professional on your data team plays a vital role in your data-driven journey, whether they are a scientist, analyst, or data engineer. However, we understand that hiring a full team and implementing the necessary tools and infrastructure can be highly expensive, but that is not the only way to secure this process… Another alternative, which has been widely adopted in the market, is hiring specialists who offer BI and data solutions, outsourcing a full data team to guide your company through all stages of data maturity. Companies like Erathos offer this service through a proprietary, highly scientific methodology to help you generate value from your data in record time.