Senior Product Analytics Engineer - Ads

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.

About the Role

Ads is one of the fastest-growing and most strategically important parts of Faire's business, and the Ads Data team 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.

What You'll Do

• Lead the design, implementation, and optimization of end-to-end and scalable data pipelines and models for a domain defining the architecture, feature requirements, and 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 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 experience within the 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.

Work Arrangement

Hybrid employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing. Additionally, hybrid in-office roles have the flexibility to work remotely up to 4 weeks per year.