Senior Software Engineer - Data Products

Senior Staff Software Engineer - Data Products About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.

Based in San Francisco, CA, Rippling has raised $1.2B from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.

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The Data Platform team works on building the blocks that are used by other teams at Rippling to create advanced HR applications at lightning fast speed. At the core of our technological aspirations lies this Team, a group dedicated to pushing the boundaries of what's possible with data. We architect high-performance, scalable systems that power the next generation of data products - ranging from reports, analytics, customizable workflows, search, and many new sets of products and capabilities to help customers manage and get unprecedented value from their business data.

We’re tackling some of the most complex and rewarding technical challenges at scale—and we need you to lead the charge. As a Senior Staff Software Engineer, you’ll be a pivotal figure in shaping the future of our engineering organization. You’ll take on ambiguous, high-stakes technical problems that span multiple teams and guide them to elegant solutions. You’ll architect robust systems, mentor engineers, and ensure our organization is aligned with cutting-edge industry standards.

This role isn’t just about code—it’s about impact. You’ll collaborate with senior leaders, drive multi-year strategies, and set the bar for engineering excellence.

• Technical Leadership:
• Lead the design and development of scalable, internet-scale distributed systems.
• Architect and build extensible solutions, from HRIS data pipelines to high-performance OLAP systems.
• Define the technical vision and ensure alignment across teams, influencing the direction of the organization’s architecture.
• Take ambiguous challenges, translate them into actionable plans, and execute with precision.
• You will be expected to dive in deep and emerge with a written plan for execution that represents the collective needs of multiple teams
• Elevate the Engineering Bar:
• Mentor and coach engineers across the org, fostering a culture of excellence and learning.
• Act as an incident commander for engineering-wide events, ensuring swift and effective resolution.
• Advocate for Performance, observability, tech debt reduction, and scalable architecture with pragmatic tradeoffs.
• Develop APIs, data pipelines, and systems using Python, Golang, Mongo
  
  DB, Kafka, and more.
• Build the future of data analytics and data insights leveraging cutting-edge technologies.
• Contribute to developing custom programming languages and tools that push the boundaries of data management.

• Experience That Speaks for Itself:
• 12+ years in software engineering, with a track record of leading technical initiatives for distributed systems at scale.
• Deep expertise in scalable architectures, resilient systems, and modern observability practices.
• Proven ability to mentor engineers, influence cross-functional teams, and sync with senior leaders to shape engineering strategy.
• A natural knack for documentation and knowledge sharing that inspires those around you.
• Master of designing systems that handle millions of users with high availability and reliability (99.99% or higher).
• Skilled in designing APIs and backend systems that make developers’ lives easier.
• Bonus Points:
• Contributions to open-source projects like Apache Iceberg, Presto, or Spark.
• Hands-on experience with OLAP stacks, query translation, or streaming systems like Kafka and Flink.

198, USD per year (US Tier
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