Data engineers need to have a holistic view of a company—because they’re impact is felt across it. They’re in the front end, the back end, and everywhere in-between. They’re in constant interaction with facets in the company as well as people who exist outside the flow chart—like customers. Let’s look at how they interact:
PAR TO INSERT DIAGRAM
Data engineers set up artificial intelligence to interact with web and app users to gather data.
Data scientists, business analysts, executives
The data is organized and prepared for analytics in a way that’s easily consumed and interpreted. Data engineers reduce human input that can cause errors by automating the pipeline. Fewer errors means cleaner data. Cleaner data moves through algorithms more easily. It draws up a clearer picture for executives to make decisions that impact the entire company. Data engineers are the ones who provide that cleansed data to the data scientists, business analysts, and executives.
Data engineers create the systems that lock data into secure storage areas. It’s important that the data pipeline is optimized—meaning it’s formatted and compressed so it can be unlocked and accessed as swiftly as possible.
Sales, CRM, HR, etc.
Each arm of a company has its own software that serves its own goals. Data engineers make sure that software is integrated into their system so the data can be accessed, stored, and shared.
Want to see how it works for Lyft? Click here.