Ascend.io, the data engineering company, announced results from a new research study about the work conditions of data scientists, data engineers, and enterprise architects in the U.S. Conducted in June 2020, findings from over 300 professionals reveal key insights on their teams’ current workload, productivity bottlenecks, and perspectives on automation and low-code technologies. Since the onset of the COVID-19 pandemic, the majority (78%) of data professionals have been asked to take on responsibilities outside of their core job function, with 97% now signaling their teams are at or over capacity. To support their teams and increase overall capacity, 89% of data professionals are turning to automation, low-code, or no-code technologies, with 73% citing automation as an opportunity for career advancement.
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Pressures on Data Teams Escalate
The overwhelming majority of data teams are currently at or over work capacity, with just 3% citing they have extra capacity for new projects. Moreover, data executives (including VPs and directors) are nearly two times more likely to indicate their teams are overloaded than team leads and individual contributors themselves, signaling a significant backlog and increasing demand by the business. When asked which team was the most backlogged, enterprise architects led the way, followed by data engineers. However, respondents were over 3.5 times more likely to identify their own team as the most backlogged over others. Despite pointing to their own team as the backlog, the research found compelling patterns emerging around the need for data engineering resources to complete their work.
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All Roads Lead to Data Engineering
Slow iteration cycles in data teams lead to significant delays for downstream users and decision makers, hindering teams’ ability to meet the data needs of the business. The delays vary by role: data scientists are mostly impacted by having to ask others for access to data or systems (48%), whereas data engineers are mostly held back by maintenance of existing and legacy systems (54%).
“Organizations are quickly discovering that data engineers are essential to unlocking the value of data and to removing bottlenecks across the entire data team,” said Sean Knapp, CEO and founder of Ascend.io. “LinkedIn’s 2020 Emerging Jobs Report found that data engineering has surged onto the scene, quickly becoming one of the top-ten jobs experiencing tremendous growth. At present, there are simply not enough data engineers to meet the demand. To enable more data professionals to tackle the growing backlog of data engineering tasks, tools such as automation, low-, and no-code technology can provide tremendous leverage and scalability for existing data engineers, while at the same time enabling a new era of citizen data engineers.”
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