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About the role

The Analytics Platform team is responsible for providing comprehensive, accessible cross-application data insights across the customers' organization. Our products include reporting, dashboards, data analytics, etc. which help customers view, understand and use their data to make informed business decisions.

This engineering role will be responsible for building the foundation that powers the Analytics platform at Rippling. You will be responsible for leading large-scale cross-org projects that touch many parts of the stack and have implications both on the long term of the engineering org as well as the business. There are challenges for the team to build for scalability to massive scale, and to platformize our products with a unified and consistent experience.

This is a unique opportunity to work on both product and platform layers at the same time. We obsess over the scalability and extensibility of platform solutions, ensuring that solutions will meet the needs across the breadth of Rippling's product suite, along with the applications of tomorrow. The Analytics Platform is a highly visible team that collaborates closely with many product and engineering teams across the organization.

What You'll Do:

Be a technical subject matter expert, provide technical leadership and share your expertise with a growing team of engineers

Continuously raise our standard of engineering excellence by implementing and driving best practices for coding, testing, and deployment

Interact with customers and support them in being successful with Rippling

Influence technology selections and trends of the whole company

Qualifications:

7+ years of software engineering experience, with 4+ years in technical lead or architect roles

Experience building large-scale distributed systems, such as high-volume SaaS environments

Experience in distributed processing engines and distributed databases of large-scale data sets

Excellent ability to communicate complex technical ideas with clarity and precision in written and verbal modes across multiple functional teams

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