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Staff Data Engineer - San Francisco California
Company: Rippling Location: San Francisco, California
Posted On: 01/25/2025
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.We prioritize candidate safety. Please be aware that official communication will only be sent from @ Rippling.com addresses.About The RoleWe are looking for an experienced data engineer to join our fast-growing data engineering practice. As a senior member of the team, you will be leading the design and development of data pipelines and services to enable data-driven decision-making, and power BI, ML, experimentation, and user-facing features. You are expected to work closely with stakeholders across a variety of orgs, such as Data Science, Marketing, Bizops, Revops, Finance, and adjacent data teams to drive projects forward and support the professional development of junior team members.Here's an idea of some of the initiatives you could be working on: - Building custom data pipelines using Airflow and AWS resources
- Setting up high-velocity data streaming consumers
- Regionalizing our data infrastructure and services
- Building out a data masking and suppression system for handling sensitive dataWhat You'll Do
- Architect, build, and scale our data pipelines for ingesting data from internal databases and systems, and third-party tools into our warehouse
- Help build out our data lake and real-time infrastructure and tooling on AWS
- Support analytics, data science, machine learning, and business operations functions
- Monitor and maintain pipelines and infrastructure to uphold internal SLAsQualifications
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