Intuit is seeking a Staff Software Engineer to join their Core Platform Engineering Team, specifically the Numaflow Team. This role focuses on an Intuit-led open source project dedicated to real-time data processing. The position involves developing and maintaining Numaflow, a cutting-edge open source project for real-time streaming and batch data workloads.
As a Staff Software Engineer, you'll be responsible for building new features, optimizing performance, and enhancing the scalability of Numaflow. This platform is crucial to real-time data processing systems that power Intuit's flagship products including TurboTax, QuickBooks, and Mailchimp, as well as several internal platforms.
The role encompasses all aspects of platform development, from initial deployment to service adoption, configuration, optimization, and troubleshooting. You'll be contributing to the ongoing development and growth of the Numaflow open source project by designing and delivering Kubernetes-native solutions for scalable real-time data processing systems.
Key technical requirements include expert knowledge of Rust and Java, with C/C++ knowledge being a plus. While AWS familiarity is beneficial, the primary focus is on Kubernetes-based platforms. You'll be working in a collaborative environment, interfacing with both internal teams and the open source community to drive innovation and maintain high-quality standards.
The position offers a competitive compensation package ranging from $184,500 to $266,500 depending on location and experience, plus additional benefits including equity, bonuses, and comprehensive healthcare. This is an excellent opportunity for experienced engineers passionate about open source development and looking to make a significant impact on large-scale financial technology systems.
Working at Intuit means joining a company that powers prosperity for approximately 100 million customers worldwide through innovative financial technology solutions. The company maintains a strong commitment to pay equity and conducts regular comparisons across categories of ethnicity and gender to ensure fair compensation practices.