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Director of Engineering - Data Pipelines & Platform

Rippling

Rippling

San Francisco, CA, USA
Posted on Friday, October 6, 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:

Join our fast-growing B2B startup as the Director of Engineering, Data Pipelines and Platform, and be a vital part of our rapid expansion. In this role, you will lead a dynamic team of engineers responsible for data pipelines and platform development. 
Your work will not only impact a diverse group of data consumers, including skilled data analysts, scientists, and machine learning engineers but also contribute to our technically advanced data infrastructure.

What you will do:

  • Lead and manage a team of talented engineers responsible for data pipelines and platform development.
  • Design, implement, and maintain scalable data pipelines to support business analytics and machine learning needs.
  • Collaborate with cross-functional teams to understand and address business stakeholders' data requirements.
  • Ensure the reliability, security, and performance of our data infrastructure.
  • Stay up-to-date with industry best practices and emerging technologies to drive continuous improvement.
  • Foster a collaborative and innovative engineering culture within the team.

What you will need:

  • Proven experience leading and managing engineering teams in a high-growth startup environment.
  • Strong background in data engineering, data pipelines, and data platform development.
  • Experience with supporting data infrastructure for machine learning applications is a plus.
  • Proficient in SQL and Python; 
  • Experience with DWH Platforms (e.g. Snowflake, Big Query or Redshift);
  • Experience with Data Infra and Storage (e.g. S3, Spark, Hadoop, Kafka); 
  • Expertise in building and optimizing data pipelines, architectures, and data sets; 
  • Experience with machine learning techniques and large foundation models,
  • Excellent communication skills to work effectively with business stakeholders.
  • Ability to thrive in a fast-paced, dynamic startup environment.

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.