Big Data Engineer Responsibilities

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Big data engineering and analytics are revolutionizing the way companies do business. By leveraging data collection on an unprecedented scale, companies large and small can use advanced analytics, machine learning, and other technologies to significantly improve their business processes.

This is made possible by the work of big data engineers. By designing and creating systems that use this data and turn it into actionable insights, prescription recommendations, and predictive models, trends, patterns, and analytical depth are used to direct process improvement and inform decision-making among entrepreneurs and new business leaders. But what does a data engineer do?

What do Big Data Engineers Do?

While many formal training programs for big data engineering have come online in recent years, the field is a collection of training, skills, knowledge, and ever-improving capabilities that drive an extensive list of roles and responsibilities. These skills include deep statistical knowledge, advanced programming skills across multiple programming formats, hands-on big data project management, database and data warehousing experience, data mining knowledge and training, and more. Here are a few big data engineer roles and responsibilities:

Data Collection

In the past, data collection was an intensive task that resulted in siloed data in on-premises servers. Data collection is one of the primary functions of a big data engineer. Cloud-based systems and direct connectivity to machines, equipment, and devices and the arrival of advanced analytics through AI and machine learning have made that data more accessible. It also vastly increased its volume.

Designing Data Architecture

Data architecture is the skeleton built on all the analytics, cleansing, and contextualizing of data. This includes the need for extensive experience in database creation and database management, especially relational databases. Data architecture consists of the models, collection standards, storage, usage, and policies that organizations use in their business.

Business Research

Just having the data isn’t enough. Companies need that data to be relevant to their business model, add value to their processes, and offer insights into product or service improvements and new product pathways. Data engineers look for new sources of data within the company’s existing assets. They also research how to obtain that data and what equipment, devices, or connectivity are required. And, once a new data source is acquired, they determine how to integrate the collection and relevant data sets into the company’s existing data architecture for use by decision-makers and staff.

Data Modeling

Advanced analytics driven by AI offers the ability to create descriptive, predictive, and prescriptive insights. This requires data engineers to design ways to identify historical patterns or glean insights from current data states to predict future behavior. From data modeling, companies can take advantage of more accurate and precise forecasting. They may also be able to develop predictive maintenance strategies for equipment or field service units. Or they may be able to identify microtrends that were invisible to human analysis alone.


Big data engineers also work to find ways for business processes to be automated. Tasks that humans performed in the past can now be detected and implemented faster for improved quality and efficiency. At the factory level, this may include robotics or autonomous machine decision-making. For field service companies, fleet maintenance, logistics, and other tracking mechanisms can be automated. The data derived from the automation is put through an analytics engine to reveal even more information.

These are just a few of the essential roles and responsibilities of a big data engineer. At the Henry Bernick Entrepreneurship Centre (HBEC) at Georgian College, we understand how the value of big data and big data engineers can affect entrepreneurs’ businesses. Our highly experienced staff can offer training, mentorship, R&D assistance, innovation, and more to companies looking to leverage the skillsets of a big data engineer or to those looking to add value and competitiveness to their enterprise using the data these professionals manage. Contact us today to learn how we can help you identify and pursue better innovation for your business using the best of big data’s benefits for your company.

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