A Data Engineer’s Guide to Integrating with Third-party APIs

There’s no escaping third-party integrations, every company has applications they use from vendors that need to read and write data. If you’ve ever had to implement these, you know how brittle and tricky they can be. So, we’ve collected best practices from experts who have learned lessons the hard way—so you don’t have to. 

After reading this guide, you’ll have a better understanding of what it takes to build third-party integrations, the common pitfalls and trade-offs to consider, the various architectures and approaches, and all the steps needed to fully build out your service. 

This guide is intended for a technical audience, with prior experience in software engineering and coding. The guide itself is language-agnostic but will provide some examples in Python as needed.

Read the Data Engineer’s guide to learn:

1. What is a third-party API and why to integrate
2. Core challenges with third-party APIs
3. The three concerns with data systems 
4. Architectural patterns for data ingestion 
5. Why you should build on top of a data warehouse