By Daniel Beach author of Data Engineering Central
As the landscape becomes increasingly data-driven, fueled by the rise of ML and AI, the importance of data engineering as a function continues to climb steadily year after year. Organizations now rely heavily on data to make every decision; data has become a requirement across every business unit, with the desire for more never stopping.
However, collecting, processing, and analyzing data is never clean, clear, or easy. That's where data engineering comes in. Data engineers have become the backbone for building and maintaining the infrastructure and tools necessary to collect, store, and process the increasing size and velocity of data being produced every second. There has never been a better time to become a data engineer or take your data engineering career to the next level.
In this blog post, we'll explore how you can become a data engineering force multiplier and significantly impact your organization's data-driven initiatives.
We will start by asserting what it means to be a data engineering force multiplier, and then unpack each one. Also, the list will be split into two sub-lists: technical and non-technical.
Architecture and technology understanding
Above-average programming skills
Good understanding of CI/CD and automation
Good understanding of testing (unit and integration)
Able to teach and upskill others
Long-term project planning and execution
Communication skills inside/outside engineering
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