Faire · Posted 3w ago
Senior Product Analytics Engineer (Ads)
Job relayed by Stapply Data, its source: you apply there.
- Location
- 🇺🇸 San Francisco, United States
- Contract
- Full-time
- Role
- Analytics engineering
- Source
- Stapply Data
The posting
Join Faire, a rapidly growing company in the e-commerce space. As a Senior Product Analytics Engineer, you will be responsible for owning the end-to-end ads data foundation and models, collaborating with cross-functional teams, and leading the integration of AI into analytical engineering. You will have a direct impact on company growth and user satisfaction.
- Lead the design, implementation, 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.
- 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