- Have attention to detail and bias for action
- Are passionate about real-time big data architecture, care deeply about customer experience, looking to work in a fast-paced environment, focusing on hard problems where the solutions are often not predefined.
- You’re autonomous, work well remotely, and a world-class communicator
- Minimum 3+ years of backend engineering work experience.
- Proficiency in writing production-quality code, preferably in Java, Scala or Python.
- Familiarity with all things building data products – schema design, modeling, optimization, scalability.
- Deep understand of real-time system, responsive API design, scalability and performance tuning.
- Excellent communication skills.
- Experience with AWS.
- Experience working with huge data sets.
- Deep understanding of Apache Spark and distributed data systems – that allows you to solve production-scale problems.
- Experience with open source development.
- Our goal is to be the dominant place to get any data on a physical Place. We sell our product – our datasets – to data scientists and machine learning engineers at companies of all sizes.
- At SafeGraph, we’ve taken a measured approach to build a long term company. We were profitable in 2019, have hired experienced leadership from the start and care deeply about democratizing access to data to everyone.
- We currently have ~70 employees and are growing quickly. We recently raised a $45 million Series B ($65 million raised to date), and the CEO was previously the founder and CEO of LiveRamp (NYSE:RAMP).
- While SafeGraph was started in San Francisco, we’ve been fully distributed across North America since 2019, and currently have small offices (in non-pandemic times) in SF, NYC & Denver. We get the entire company together in the same place as often as possible, and cannot wait to do this again soon
- We offer our employees a robust set of benefits, including health, dental & vision insurance coverage, a 401k, work-from-home stipend, mental health benefits, and much more.
- SafeGraph: about us, visions and values
- Open Information to Power Innovation
- Where Should Machines go to Learn
- Why Data Standards Matter