- San Francisco, CA
We're a San Francisco startup with Mobile, Web and Analytics products. We're growing really quickly - we went from 40 to 80+ people in the last few months and sales are growing exponentially too.
Here are a few things that make Showpad a great place to work:
- We are a fun, growing startup in downtown San Francisco
- We have over 600 customers including Intel, Audi, and Xerox.
- Based on our success, we recently got a Series B round to turbo-charge our growth
- Our customers love us. Almost 100% of our customers renew at the end of the year.
- Our founders are awesome. This is the second successful company they’ve started together.
- We have a ukulele band (called Trevor and the Ukuladies)
We're looking for engineers to own our Analytics products. This is fast evolving product with new and fun challenges every day.
This job might be right for you if...
- You're a rockstar software engineer who enjoys the challenge of building a complex web application from the ground up.
- You've used backend frameworks (such as Koa or Express) to build elegant and scalable applications.
- You want to own every aspect of the application from architecting the database schema (SQL and NoSQL), designing APIs for serving the front-end, deploying applications in production, and setting up monitoring and infrastructure tooling.
- You can tackle performance & scalability challenges from the client-side through the web application tier, all the way to the backend database.
- You are passionate about technology and love working together with like-minded smart people
If you have Backend Engineering skills, and can prove it, we’ll consider your application and tailor a role just for you. Some things that help:
- Experience as a Backend or Data Engineer at an impressive company
- Experience working on data from SaaS, Web and/or Mobile products
- Open source project contributions
- Solid understanding of relational database modeling and design, including experience building data-intensive applications
- Experience with NoSQL datastores such as Redis, ElasticSearch or similar at scale.