The Power of Analytics Engineers

In today's data-driven world, companies are collecting vast amounts of data every day, which has led to most companies having highly skilled data teams. They aim to gain insights into their customers, products, and services. Traditionally within those teams, data analysts, scientists and engineers all play an essential role with their unique skill sets to translate the data for businesses to make data-driven decisions. But, we are now seeing a rise in the ‘analytics engineer’ that is merging the technical prowess of the data engineering teams, with the business-facing insights of the Analysts. 

What is an analytics engineer?

An analytics engineer is a skilled professional who specialises in developing and maintaining data visualisation systems. They work with large and complex datasets and use various programming languages and tools to transform data into a more digestible/useable format, enabling data scientists and analysts to deliver essential insights to stakeholders.  

How can an analytics engineer help your business?

One of the main problems that businesses face when dealing with data is the lack of standardisation and consistency in their data sources. Data comes from different sources, in different formats, and with different levels of quality. This can make it difficult to analyse and interpret the data accurately. An analytics engineer can help to solve this problem by creating standardised data pipelines that ensure data is collected, processed, and analysed consistently. 

Another problem that businesses face is the need to process and analyse data in real time. This is particularly important for businesses that operate in industries such as finance, healthcare, and e-commerce, where real-time data can provide a competitive advantage. An analytics engineer can help to design and implement real-time data processing systems that provide up-to-date insights to the business.

What to look for when hiring an analytics engineer?

A highly skilled analytics engineer should have a strong background in data engineering, computer science, and statistics. They should have experience in designing and implementing data pipelines, data warehouses, and data visualisation systems. They should also have excellent programming skills in languages such as Python, SQL, and Java, and be familiar with data processing tools such as Hadoop, Spark, and Kafka.

In addition to technical skills, a highly skilled analytics engineer should have excellent communication and collaboration skills. They should be able to work closely with business stakeholders to understand their data needs and translate them into technical requirements. They should also be able to communicate complex data insights to non-technical stakeholders in a clear and concise manner.

In the years to come, analytics engineers will become even more important for businesses. As data continues to grow in volume and complexity, businesses will need skilled professionals who can help them to make sense of it all. Analytics engineers will play a critical role in helping businesses to stay competitive by enabling data analysts and scientists to produce effective insights for senior management. 

Conclusion

Businesses need analytics engineers to help them manage and analyse their data. Analytics engineers can help to solve the problems of data standardisation and real-time processing and enable insight production that can help businesses to make data-driven decisions. A highly skilled analytics engineer should have a strong technical background, excellent communication skills, and the ability to work collaboratively with business stakeholders. Analytics engineers will become even more important for businesses in the years to come, and salaries for these professionals are likely to rise as demand increases.

If you want to discuss hiring analytics engineers get in touch with our specialist consultants.