Senior Data Engineer



Data Science
San Francisco, CA, USA
Posted on Tuesday, June 20, 2023
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, Bedrock, and Greenoaks—and was named one of America's best startup employers by Forbes (#12 out of 500)

About The Role

We are looking for a hands-on senior engineer to play a key role in Rippling’s data team. As a senior engineering resource on the data engineering team, you will be leading the design and development of systems that will enable analytics, experimentation, and user-facing features. You will be closely involved with multiple data adjacent teams and stakeholders, alongside helping junior talent in the team learn and grow.

The Data Engineering Team at Rippling is a combination of warehousing and data platform engineering, supporting a variety of orgs across the company (Data Science, Marketing, Bizops, Revops, Finance to name a few). Here’s an idea of some of the initiatives we’re working on:

  • A realtime, central data lake to operationalize warehouse data.

  • Creating a metrics layer to make reporting more efficient and accurate.

  • Building a catalog to make our data assets searchable and easy to discover.

  • Making our globally distributed data stack compliant and scalable

What You'll Do

  • Help architect, build, and scale our data pipelines from our OLTP database, other internal systems and third party tools to our warehouse (Snowflake)

  • Leverage data technologies like Kafka, Presto, Flink, Airflow, Mongo, Snowflake and Spark

  • Support reporting, data science, operations and machine learning functions

  • Create data platforms, data lakes, and data ingestion systems that work at scale

  • Define and enforce data quality checks and audits for code warehousing datasets

  • Define and support internal SLAs for core data sets


  • 5+ Years experience in Data and Software Engineering

  • Expertise in writing complex data transforms in SQL and Python

  • Knowledge of data warehousing concepts around building custom ETL integrations, building data infrastructure (SCD,CDC,Snapshots,indexing,partitioning)

  • Knowledge on Data Security and Governance (nice to have)

  • Experience in analytics, dimensional modeling, and ETL optimization preferred

  • BS/BA in a technical field such as Computer Science or Mathematics preferred

Additional Information

Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accomodations@rippling.com

Rippling highly values having employees working in-office to foster a collaborative work environment and company culture.  For office-based employees (employees who live within a 40 mile radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.

This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here.

A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed below.