How Data Engineers Are Quietly Becoming the Most Important People in the Org

Successful businesses run on data. Marketing departments collect troves of customer data to connect potential buyers with the right messages. Human resources departments analyze employee data to design benefits packages that will retain top-tier talent. Executive leadership teams comb through financial data to present accurate views of their companies’ health to investors.  

But all of this data doesn’t magically organize itself; it requires skilled professionals to manage what can be mountains of vital information. Data engineers, who serve as digital gatekeepers, this role comes with the power to influence important business decisions.  

Zach Damuth, lead business intelligence consultant at RXA@OneMagnify, has worked with companies to build efficient data pipelines and address data storage issues that led to measurable improvements in their operations. His success has translated into CEOs and CFOs calling on Damuth to consult on other mission-critical projects, like evaluating potential new enterprise resource planning tools.  

“They're placing their trust in me,” Damuth shared. “In the situation where I'm operating as a pseudo data engineer, they’re saying, ‘Hey, we know that we need you to be a part of the process, and we want to hear what you have to say about how this is going to impact our data and what problems or benefits it might cause us if we choose one tool or another.’”  

Many business leaders may be overlooking the expertise of their data engineers. Instead of treating them as people who just move data around, leaders should recognize the value data engineers bring to the organization and how their behind-the-scenes work can be the foundation for every smart, timely, and scalable decision your company will make.  

And, if you’re a data engineer, it’s time to embrace your evolving role as a strategic enabler to move beyond managing infrastructure and start influencing outcomes across the business.  

What do data engineers actually do?

Despite the essential role they play for businesses, the importance of data engineers is often misunderstood by colleagues who don’t fully understand what they do. Part of the reason is many people lump data engineers, data analysts, and data scientists together. While these roles are certainly related, all working closely with data, each brings distinct skills and responsibilities.  

A simple way to think about how these three data-centric roles differ:

• Data scientists develop the algorithms and models that analyze data sets.

• Data analysts interpret and put into context the analysis results in order to make recommendations, forecasts, and predictions.  

• Data engineers lay the foundation for both by are responsible for collecting and preparing data for analysis,

Remember, you can’t get accurate and reliable results without clean, organized, and complete data sets. That’s why the success of your entire data program hinges on the engineers getting their job right—from the start.

The evolving data engineering role

So, what does getting it right look like? Data engineers have a variety of responsibilities, including:

Building out the infrastructure to collect, store, and process data. With companies collecting more data than ever before, data engineers are teaming up with IT professionals and other teams to evaluate and choose the right tools and systems. This creates the foundation for organizations to both house and analyze data at scale.

Developing pipelines to transfer data from various sources into a central location that acts as a single source of truth. Different teams have their own systems for collecting data. But if left unchecked, important information can get lost in an ever-growing list of disconnected locations. Data engineers make sure all of the relevant data collected from different teams flows smoothly into a central repository for analysis.

Transforming and cleansing data before it’s processed. When you have so many teams collecting data, there’s a good chance that the different tools they use to capture information don’t label that data in the exact same way. However, consistency in the data is the key to generating useful analysis. Data engineers address this potential pitfall head on by performing ETL (Extract, Transform, Load) processes to ensure that the data is clean and ready for use.  

Managing and maintaining databases. Everyone wants access to data. Unfortunately, all it takes is one curious person switching out a column name or date format to break your perfectly prepared data set. Data engineers prevent these costly catastrophes by granting the appropriate access to data for individuals across the company. They also collaborate with the IT team so that the right security protocols are in place to avoid potential breaches.

Finding and using strategies to improve data collection and preparation. Artificial intelligence is disrupting the way data engineers operate, and many of those changes are for the better. AI and data engineering can work hand in hand to make previously time-consuming tasks simpler and more efficient.  

For example, engineers who have a solid grasp of writing AI prompts can swiftly identify incorrect inputs in large data sets and address any potential issues before analysis is run. AI has also powered data pipeline automation so companies can to continue to pull larger quantities of valuable information into their databases without overworking their engineering team.    

Damuth points out that the biggest shift that he’s seen over the past few years in the role of data engineers is the move away from solely operating within internal systems.

“The data engineer’s job is still internally focused, but it includes working with a lot more external data now,” he explained. “So now we’re put in a different spot that necessitates different skill sets to communicate between those different systems and work in these larger more advanced environments.”

Still, he says, “the principles of data have stayed relatively the same.”

Working in this field will therefore require a solid grasp of programming languages like Python, SQL, and Java; expertise in database design and technologies like MySQL; extensive experience using data processing and ETL tools; as well as an understanding of data warehousing and cloud computing.

Growing your influence as an expert in data engineering

Of course, it’s not just the technical skills that enable data engineers to win a seat at the table for larger organizational decision-making. As any professional in tech will tell you, soft skills like communication and leadership make all the difference when trying to earn your colleagues’ trust and respect.

In a new work environment where everyone across the organization is a bit more tech savvy than they were 10 years ago, Damuth says there are still very practical ways for you to start to build your influence:

1. Be confident in your role.

Data engineers need to be shepherds of all the different data being collected from all the different sources. While your colleagues may have a more general understanding of how to generate analysis, they often don’t understand how to do it.  

So understand that you play a vital and strategic role in ensuring the integrity of your data collection and storage program. Project confidence and enter conversations as an expert in your field.  

2. Communicate proactively.

Those more tech savvy individuals in your organization will bring their own opinions to the table regardless of whether they’re rooted in relevant knowledge. But you better believe that there is still an expertise gap that you fill.  

If you want influence in your organization, you can’t be a passive player who only offers your opinion when it’s called upon. When opportunities arise to jump into the conversation, make sure you raise your hand and you’re ready to offer valuable insights.

3. Bring solutions to the table.

Those insights that you share shouldn’t always be a list of reasons why something won’t work or something will be difficult. Leaders are looking to you to solve problems and propel the company forward toward new possibilities.  

While it’s necessary to acknowledge the reality of challenges and to avoid overpromising, lead your conversations with potential solutions. It will send a message that you have the knowledge to work through puzzling challenges and the initiative to dive into any task without handholding. It’s an easy way to showcase your value and earn invitations to influence outside of your silo.  

Embrace your role by taking the lead on enterprise data strategy

There is one other way to build your influence as a data engineer—onboarding intuitive tools that make working with data easy for everyone.

Domo gives data engineers the tools to not only build scalable data pipelines, but to ensure their work is trusted, useful, and aligned with business needs. With built-in governance, monitoring, documentation, and visualization layers, engineers can turn raw data into reusable assets that fuel analytics, operations, and AI. Domo’s flexibility also supports iteration and expansion, so engineers don’t just keep the lights on; they help set the direction.  

Read more about how Domo helps data engineers increase their impact, and learn how the work you do behind the scenes can drive value across the org.