About the role
Staff Software Engineer - Data Cloud Staff Software Engineer - Data Cloud About Rippling Rippling is the first way for businesses to manage all of their HR & IT—payroll,
benefits, computers, apps, and more—in one unified workforce platform. By connecting every business system to one source of truth for employee data, businesses can automate all of the manual work they normally need to do to make employee changes. Take onboarding, for example. With Rippling, you can just click a button and set up a new employees’ payroll, health insurance, work computer, and third-party apps—like Slack, Zoom, and Office 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 Role: The Data Cloud team is building an end-to-end analytics and business intelligence system for our customers and will replace their need for Data Lakes, Data Warehouses and data pipelines. We are building systems for ingestion, transformation, lineage, data catalogs and visualization. Most companies cobble together data pipelines from Fivetran, Airbyte, Airflow, DBT, Snowflake, DataBricks, Kafka and a host of other technologies. Rippling is in the unique position of being the source of the vast majority of this data, hence we can provide an all encompassing solution out of the box. In addition, we are exploring the use of ML and LLMs to provide automated insight generation and conversational experiences to allow data consumers to have a virtual data scientist as their analytics copilot.
What You'll Do: Develop high-quality software with attention to detail using tech stacks like Python, Apache Trino, Iceberg, Temporal. Create Data visualization and query processing products used at large scale. Create data platforms, data lakes, and data ingestion systems that work at scale Have clear ownership of one or many products, APIs or platform spaces Build and grow your engineering skills in different challenging areas and solve hard technical problems Influence architecture, technology selections, and trends of the whole company
