Crunchbase is the leading destination where you can discover innovative companies, connect with the people behind them, and uncover new opportunities. Our mission is to democratize the way innovators connect to opportunities, and over 50 million professionals-including entrepreneurs, investors, market researchers, and sales people-trust Crunchbase to inform their business decisions. Companies all over the world rely on Crunchbase to power their applications, making over one billion API calls on our platform each year.
Data Engineering at Crunchbase
Our data team is responsible for building and maintaining the infrastructure for our data needs. As Crunchbase grows, so too does the amount of data we process, the number of sources it comes from, and the number of ways that people want to slice and dice it. We are currently building out a robust pipeline for our core data and we're continually expanding use cases for it, so it must be both scalable and flexible.
At its core, Crunchbase is a data company, and data engineering is at the heart of our platform and will propel us into the future.
The responsibilities of data engineers at Crunchbase include:
* Architect and build new dimensional data models and schema designs to improve accessibility, efficiency, consistency and quality of both internal and production data * Build, monitor, and maintain analytics and production data ETL pipelines * Provide the foundation for a data-driven culture by empowering other engineers and the Product team to ask questions of the dataset in an easy, reliable way * Enable data scientists to implement NLP and ML algorithms at scale, in fault-tolerant, highly available systems
Crunchbase is a company that provides a platform for finding business information about private and public companies.