Software Engineer, Graph Platform

  • Toronto, Canada
  • Employees can work remotely
  • Full-time

Company Description

Square builds common business tools in unconventional ways so more people can start, run, and grow their businesses. When Square started, it was difficult and expensive (or just plain impossible) for some businesses to take credit cards. Square made credit card payments possible for all by turning a mobile phone into a credit card reader. Since then Square has been building an entire business toolkit of both hardware and software products including Square Capital, Square Terminal, Square Payroll, and more. We’re working to find new and better ways to help businesses succeed on their own terms—and we’re looking for people like you to help shape tomorrow at Square.

Job Description

All of Square's product services are organized into departments with their own product and engineering teams. Underneath, there's a connected platform team that supports the network. We are that platform. Through data pipelines, we collect data from across Square's ecosystem of products. Our knowledge graph infrastructure contains billions connections between millions entities across Square. This connected data is used across multiple teams, from getting more users onto the Square platform to feature development for statistical models. The scope of this team's work is expanding and there are many opportunities for improving Square's growing global audience.

Within our team, we're looking for engineers to focus on building Square's graph data systems. Our focus is on building fault tolerant systems that make operations, analysts and data scientists happier and more productive. Our infrastructure is used by product teams on both the Seller and Cash App sides of the business.

You will build APIs and databases that connect data from products across Square. You will work with our internal customers (Machine Learning Engineers, Data Scientists and Operations Agents) to understand their workflows.

Qualifications

  • A desire to design systems that solve our customer's problems; you want to understand your customers' needs.
  • You lead small projects and mentor junior engineers
  • The ability to produce production-quality code incorporating testing, evaluation, and monitoring
  • 5+ years of experience developing large-scale distributed data systems
  • Experience using any of the major cloud vendors (GCP, AWS, Azure)
  • Experience in any of: graph or network data, machine learning infrastructure
  • It is a plus if you have an advanced degree focusing in computer science or other computational fields.

We use and teach:

  • Java, Python, Google Cloud Platform, AWS, Snowflake, JanusGraph, and Docker
  • MySQL, Redis, Hibernate, jOOQ, and Bigtable
  • Python ML stack (pandas, scikit-learn, Jupyter, TensorFlow)

Additional Information

At Square, our purpose is to empower – within and outside of our walls. In order to build the best tools for the businesses and customers we support all over the world, we have to start at home with a workforce as diverse and empowered as our sellers. To this end, we take great care to evaluate all employees and job applicants equally, based on merit, competence, and qualifications. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage candidates from all backgrounds to apply. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible.

Perks

At Square, we want you to be well and thrive. Our global benefits package includes:
  • Healthcare coverage
  • Retirement Plans
  • Employee Stock Purchase Program
  • Wellness perks
  • Paid parental leave
  • Paid time off
  • Learning and Development resources
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