Rippling
Staff Data Engineer
Rippling, San Francisco, California, United States, 94199
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.
We prioritize candidate safety. Please be aware that official communication will only be sent from @ Rippling.com
addresses.
About The Role
We 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 data
What 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 SLAs
Qualifications8+ years of 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, and building data infrastructure (SCD, CDC, Snapshots, indexing, partitioning)
Knowledge of 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.#J-18808-Ljbffr
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 Role
We 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 data
What 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 SLAs
Qualifications8+ years of 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, and building data infrastructure (SCD, CDC, Snapshots, indexing, partitioning)
Knowledge of 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.#J-18808-Ljbffr