Job description

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this role Ads is one of the fastest-growing and most strategically important parts of Faire's business, and the Ads Data team — now three years old — is entering a period of hypergrowth. As a product analytical engineer, you will own the end-to-end ads data foundation and models. You will partner closely with cross-functional teams in Product, Engineering, ML Applied Sciences, and Strategy & Analytics (S&A) to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve data consumption workflows, and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. Join us and be part of a team that values data-driven innovation and excellence. What you’ll do The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. Lead the design, implementmentation, and optimization of end-to-end and scalable data pipelines and models for a domain defining the architecture, feature requirements, roadmap. Collaborate with engineers, product managers, S&A, and ML applied scientists to translate business requirements into production-grade data systems and insights. Build and maintain data infrastructure, pipelines, and models that ensure data quality, consistency, and accessibility for analytical workflows. Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows. Mentor team members on best practices for scalable data engineering and quantitative problem-solving. Ensure and promote data quality standards for accurate and reliable insights. Embrace emerging technologies with enthusiasm. Qualifications 4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases. Preferred experiences within Ads domain. Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders. Production-level development experience in Python. Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance. Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms. Experience with Airflow, Docker, DBT or similar analytics workflow tools. Bachelor’s or Master’s degree in Computer Science, Math, Physics, or a related technical field. Salary Range California: the pay range for this role is $ 196,000 to $ 269,500 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Why you’ll love working at Faire Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog . Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form ( bit.ly) Privacy For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (faire.com)

Requirements

Must-haves

Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.
Production-level development experience in Python.
Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.
Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.
Experience with Airflow, Docker, DBT or similar analytics workflow tools.
Bachelor’s or Master’s degree in Computer Science, Math, Physics, or a related technical field.
Why you’ll love working at Faire
Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.
Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.

Nice-to-haves

4+ years experience in analytics & data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases. Preferred experiences within Ads domain.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: greenhouse
Effort: quick