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A data engineer is currently the most sought after tech job–– it had an 88.3% increase in postings over the past twelve months according to Burning Glass’s Nova platform. Why? The answer is hidden in the apps you rely on every day: data streaming.
Right now, you probably have a handful of apps on your phone that leverage real-time data––think ride-sharing apps, maps, and streaming services. And that’s just skimming the surface. Financial institutions use data streaming to monitor the stock market and hospitals use streamed data to monitor the health of patients. In a nutshell, data streaming is the process of sending data continuously rather than in batches, which enables millions of companies to create the products we use every day. This includes everything from web personalization and recommendation engines, to fraud detection and in-game interactions.
The data streaming job market
The International Data Corporation (IDC) projects the big data and analytics industry to be worth $189.1 billion in 2019, which is a 12% increase from 2018. The most in-demand engineers in this job market will be equipped to help companies manage the transition to data streaming. Nathan Tatum explained in a CapTech blog that, “Time is money. Capturing data and making it available within an organization quickly will be a differentiator for companies in the modern data architecture.”
As of September 2019, there were about 20,000 open jobs for Data Engineers in the US & Canada and about 14,000 in the EU. According to Glassdoor, the national average salary for a Data Engineer in the US is $116,591.
Why companies rely on data streaming
Data engineers are able to collect and make sense of dynamic data, enabling almost all other data-related actions to take place. That makes data engineers incredibly crucial to a company’s data analytics strategy. They build data infrastructure, including data warehouses, data lakes, and data pipelines, and make data accessible for other members of the organization. Without these systems, data sits in a data center and simply takes up space. It’s no wonder companies want to take advantage of this data and put it to valuable use.
Mark Brewer, CEO at Lightbend, said “We see a renaissance right now where developers are being asked to be a lot more ‘data smart.’” “Streaming data is table stakes for the most interesting future use cases––Artificial Intelligence and Machine Learning most notably––and that’s giving rise to the number of programming languages, frameworks, and tools for building and running streaming data-centric applications.”
As businesses increasingly rely on applications that produce and process data in real-time, data streaming will continue to be an in-demand skill for data engineers. Udacity’s Data Streaming Nanodegree comes at the perfect time, allowing data engineers and software engineers to get a leg up in advancing their careers as more companies look to derive live insights from data at scale.
Who should learn data streaming?
Udacity’s Data Streaming Nanodegree is intended for software engineers looking to build real-time data processing proficiency, as well as data engineers looking to enhance their existing skill-set with the next advancement in data engineering.
The projects in the Data Streaming Nanodegree program prepares students to develop systems and applications capable of interpreting data in real-time, positioning them for roles in all industries that require live data processing for functions including big data, cloud computing, web personalization, fraud detection, sensor monitoring, anomaly detection, supply chain maintenance, location-based services, and much more.
Undoubtedly, data streaming is in demand more than ever and is increasingly becoming a lucrative skill for engineers to master. Since data streaming is crucial to almost every type of business, this demand is only going to increase.
Interested in understanding how data streaming can advance your career? Get an in-depth look at Udacity’s Data Streaming Nanodegree program.