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Senior Product Analytics Engineer (Ads)

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Onsite

Senior Product Analytics Engineer (Ads)

Faire

Senior Product Analytics Engineer (Ads)

Skills

SQL QueriesBig DataData EngineeringDockerPythonData ScienceData AnalysisMachine LearningAIdbtApache Airflow

17 days ago

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Important information


Contract type:

Permanent

Salary:

$196,000 – $269,500 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

4 October 2026

What they need


  • 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
  • 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

Benefits

  • Comprehensive healthcare: Including Health, Dental, Vision and Disability for all our locations.
  • Time off: Paid time off, holidays and company-wide “Faire Fundays”.
  • Parental leave: Generous parental and family leave, as well as fertility support benefits.
  • Productivity support: Monthly stipends to help cover work from home connectivity needs.
  • Annual learning grant: For personal and professional development, as well as unlimited access to training courses through LinkedIn Learning.
  • Thoughtfully designed spaces: All of our offices have been designed with local in mind – from our architects to our coffee blends.
  • Fitness and well-being benefits: Including monthly credit towards your wellness-related programmes.
  • Mental health benefits: Including free access to Modern Health therapists and resources.
  • Charitable matching: Faire will match up to £250 of your charity donations, every year.
  • Career planning: Whether you want to grow as a leader, hone your craft or explore a new discipline, our career framework allows space for you to explore.- 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
  • Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders
  • Experience with Airflow, Docker, DBT or similar analytics workflow tools
  • 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
  • Production-level development experience in Python
  • Bachelor’s or Master’s degree in Computer Science, Math, Physics, or a related technical field
  • 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

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