Data engineering: a role redefined by business needs and interpersonal skills 

Programming, coding, cyber

Shadi Rostami looks at the role of a data engineer, and it’s not just numbers. Communication and a business mindset are crucial for a role that’s increasingly important for L&D teams 

While companies today have vast, continually expanding data sources, most don’t fully comprehend the extent of their data’s value, nor the critical role it plays in driving business decisions. This is where data engineers come in, a role among the fastest growing within the UK job market.  

By cultivating a blend of technical prowess and interpersonal capabilities, data engineers can propel their careers forward 

Landing the position of data engineer requires more than just the important technical know-how and role-specific skills. To truly excel as a data engineer, a person must be able to empathise with their clients and the problems they are helping to solve. Here’s how to secure the role. 

The day-to-day of a data engineer  

The main part of a data engineer’s role is – you guessed it – data. Data engineers design, manage and optimise data flows while building data pipelines for business analysis. Beyond this collection and curation, data engineers also empower organisations with self-serve data that can be easily accessed.  

Collaboration is another key element of the role, and data engineers often work with data scientists, and teams such as marketing and product, to drive data-driven decision-making company-wide. Essentially, data engineers form the bridge between data insights and non-technical personnel. 

The roles and responsibilities of a data engineer are extremely varied and often depend on the size of an organisation, as well as what services it offers. Still, there are several essential skills that are key to success in this role: 

  • Analytics: Understanding modern data stacks and tools used by key departments. 
  • Data management: Data governance expertise and pipeline management know-how. 
  • Data integration: Understanding of extract, transform, load (ETL) or extract, load, transform (ELT). 
  • Data modelling: The ability to accurately model data structures and relationships. 
  • Databases: Understanding of data lakes, as well as knowledge of SQL and NoSQL databases. 
  • Programming: Expertise in languages such as Python, Java, and C++. 

However, as much as they are important, mastering these skills will only take a person so far. The role of data engineer is full of nuances, many of which can be learnt through experience on the job. As new optimisation methods emerge, these skills continually evolve, so remaining open-minded and willing to adapt will be crucial. 

Don’t forget soft skills 

Technical skills are important for this role, that’s a given. But something that many people forget is that soft skills, such as communication, empathy and collaboration, are equally vital for becoming a well-rounded data engineer. 

First off, there’s the skill of communication. Effective data engineers play the role of a translator who interprets data for teams, customers and partners. Armed with the right soft skills, these individuals can closely partner with business units to communicate the data insights that are crucial for internal and external business operations. This understanding allows engineers to build systems that enable specific teams, including product and marketing, to swiftly and accurately self-serve. 

Empathy is another critical soft skill for data engineers. Those who interact with customers have an opportunity to not only solve complex problems faster, but also gain a better understanding of customers’ business goals. With that knowledge, data engineers can proactively serve customers as a true partner, not just a vendor. 

For aspiring data engineers, collaboration is another key skill to build. It’s vital that data engineers aren’t working in silos, but are communicating with everyone within an organisation, from product teams to data scientists. By openly communicating and sharing data insights with other teams early in the process, data engineers ensure everyone is aligned with the same company goals.  

Embrace a business-first mindset 

Finally, data engineers must adopt a business-first mindset. Engineering decisions cannot be made simply through the lens of that specific job title. Instead, engineers must think big, asking themselves what the implications will be for the entire company, not just their department. The ability to think beyond the responsibilities of a data engineer is vital for career success.  

Let’s take a look at this in practice. An engineering colleague created analytics dashboards to understand which customers may benefit from the product they’re working on. This is not within this person’s scope of work, but in doing so, they established relationships with the customers their dashboards highlighted so they could understand their pain points better. This is above and beyond the role of a data engineer, and the mark of a true owner.  

In today’s data-driven world, data engineers are crucial and companies rely on them. But always remember that, to excel as a data engineer, it is not just technical expertise that matters. While an engineer can master the art of programming, data modelling, and understanding data tools and pipelines, they must also cultivate their soft skills simultaneously.  

By cultivating a blend of technical prowess and interpersonal capabilities, data engineers can propel their careers forward as indispensable assets driving organisational success through data. 

Shadi Rostami is Senior/Executive VP of Engineering at Amplitude 

Shadi Rostami

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