Emily loves to be involved in a range of things from blowing up circuits to riding horses to rockets. She's an Electrical Engineer by trade but has found herself working in the realms of software and data science. With a passion for both hardware and software, she hopes to combine the two to make technology smarter and more sustainable. Currently, she is leading engineering at Multitudes, a startup providing engineering metrics that aren’t creepy to unlock happier and higher-performing teams.
What makes a data integration great for data engineers and what makes a terrible one? At Multitudes, Emily's had to integrate with data from companies big and small; Jira, Linear, Pagerduty and GitHub just to name a few! Some integrations were better than others. What lessons can we learn from how these companies built their data integrations (or how NOT to) and what can we take away to help us as data engineers work more seamlessly with development teams? Emily's spent time both as a backend developer and a data engineer. Therefore, she has a unique understanding of both development and data team's challenges when it comes to data pipelines. We'll look into some common ways that companies allow you to integrate with them and what constraints there can be on the data that is retrieved. From this, Emily will outline some basic steps data engineers can take when working with data from new sources. These lessons will apply to not just data integrations, but also how to better work with your development team to get the data you want.
Starts: 11:40 AM
Ends: 12:10 PM