Senior Data Engineer

Why join Pave? At Pave, our vision is simple - Make Compensation Fair.

Do not pass up this chance, apply quickly if your experience and skills match what is in the following description.

How are we going to get there? By building the most intelligent compensation platform, powered by the largest real-time compensation dataset on earth.

We partner with our customers to help them build and retain world-class teams through planning, communicating and benchmarking their team’s compensation in real time.

And you don’t have to just hear it from us you can hear it from our customers : Allbirds, Hover, Sweetgreen, Airtable and more.

We’re growing fast, building an incredible team and product, and having plenty of fun as we do it in our San Francisco and New York City offices.

If stretching the rubber band, building with intellectual honesty and focusing on impact sounds exciting - we highly encourage you to reach out.

We’d love to partner on our journey to change the world of compensation!

Data Science @ Pave

The mission of the Data team at Pave is to leverage the rich data produced by the Pave ecosystem to enable Pave to provide the most valuable insights to its users as well as to serve as the core optimization engine for the company.

We build data infrastructure, define and evaluate metrics of success, derive actionable insights, and build predictive models to enable a culture of data-driven decision making and optimize every aspect of our business.

What you'll get out of it :

• Creating and maintaining data pipelines to support analytics, metrics reporting, machine learning, product features, and more
• Collecting and synthesizing business requirements, to ensure our infrastructure aligns with and enables our data and business strategy
• Designing and maintaining our data warehouse, and documenting architectural decisions to enable collaboration, scalability, and usability
• Maintaining and developing tooling to support our Data team
• Powering our product roadmap by ensuring reliable access to quality data
• Collaborating with our integrations team to unify data from multiple sources
• Driving technical excellence across the entire Data team

What we're looking for :

• 4-6+ years of experience in a data engineering or similar functional role
• Bachelor’s degree or advanced degree in a quantitative discipline : Computer Science, Math, Statistics, Engineering, or a related field
• Expert knowledge of Python and SQL
• Expert knowledge of development best practices including query optimization, version control, and documentation
• Experience maintaining and proactively optimizing data pipelines and ETL processes
• Experience developing robust data models
• Experience implementing monitoring and data quality assurance frameworks
• Exceptional knowledge of data warehouse design and management
• Experience with modern data storage and processing techniques (e.g., Airflow, BigQuery, DBT, or similar)
• Strong communication skills
• Comfortable working in fast-paced environments
• Ability to lead strategically across data and software engineering teams

Our Compensation Philosophy Pave’s compensation philosophy is to target the 75th percentile of the market for both cash and equity at your job level.

This means that the mid point of every band at Pave is the 75th percentile of the broader market.

Pave also has a merit-based philosophy when it comes to compensation increases. We run a performance cycle twice per year to evaluate employees’ performance.

Higher than average performance ratings result in compensation increases to the upper end of the individual’s compensation range for their role.

The result is that high performers at Pave are paid above the 75th percentile of the market at large.

Pave is committed to pay equity. If you get an offer from Pave, it will be based on your level as determined by your interview performance.

And nothing else. We explicitly do not negotiate salary and equity to ensure that we aren’t introducing bias that could lead to pay inequities within the team between candidates who have different negotiation tactics.

FAQ’s :

• How big is Pave today? We were founded in late 2019, and have grown to 160 employees across San Francisco, New York and the UK.
• Where are the Pave offices? Our company HQ is in San Francisco's FiDi with a high energy in-person culture. We also have an office in NYC and a hub in England.
• What do employee benefits at Pave look like? As an employee at Pave, you will have your choice of medical, dental and vision insurance, as well as access to mental health services and other perks to promote your wellbeing.

To enhance your personal and professional growth, you will have a monthly L&D stipend. We take our snacking seriously - employees receive catered lunch, dinner and many fun snacks throughout the day.

• Who are some of Pave’s customers? Pave is working with 5,500+ companies today, including some of the best technology logos out there like Credit Karma, RO, Faire, Dropbox, Airtable, Sweetgreen, Checkr, Hubspot, Snackpass, Attentive and more!
• What can I expect in interviewing at Pave? At Pave, we value intellectual honesty and transparency, and we bring this to our interview process.

Throughout your time interviewing with us, we will be evaluating where you can best make an impact through multiple conversations with your recruiter, hiring manager, peers and cross-functional partners.

We also use our interviews to determine leveling, which is finalized at the end of your interview process by your hiring manager.

The majority of our roles have 3-5 interview rounds. You can expect to hear back from our team within 7 days of application, as well as within 2 days after each interview round.

Once we extend an offer, we hope to hear back from you within 1 week. It is extremely important to us that we find a great mutual fit - we’re excited to get to know you!

More Questions? Check out our candidate resources page!

Pave is committed to a diverse and inclusive workforce. We are an equal opportunity employer and do not discriminate on the basis of race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or another legally protected status.

For individuals with disabilities who would like to request accommodation, please email [email protected].

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