Analytics Engineer - Ads Data & AI Pipelines | Faire

Ads is one of the fastest-growing and most strategically important lines of business at Faire. As a Product Analytical Engineer on the Ads Data team, you will own the end-to-end data foundation, data pipelines, and analytical data models powering Faire’s advertising products. Partnering closely with Product, Engineering, ML Applied Sciences, and Strategy & Analytics (S&A), you will design and deploy production-grade data capabilities that inform business metrics, power ad performance insights, and support rapid product rollouts. In this role, you will also lead the adoption of AI tools within analytics engineering—leveraging AI to automate routine data pipeline tasks, streamline data consumption, and enhance data quality across Faire's ads platform.

Key Responsibilities

Ads Data Architecture & AI Pipeline Engineering

• End-to-End Ads Data Foundation: Lead the design, implementation, and performance optimization of end-to-end, scalable data pipelines and data models tailored specifically to the Ads domain.
• AI-Driven Data Operations: Transform analytics engineering workflows by embedding AI tools into daily operations—streamlining pipeline development, automating ETL processes, and improving data consumption.
• Production-Grade Data Infrastructure: Build and maintain high-performance data infrastructure, ensuring data quality, consistency, accessibility, and strict validation across analytical workflows.
• Data Quality & Governance: Establish, champion, and enforce data quality and validation standards to guarantee reliable metrics and actionable insights for business leadership.

Cross-Functional Collaboration & Team Leadership

• Cross-Functional Alignment: Translate complex business and product requirements into production-grade data systems by partnering with Software Engineers, Product Managers, Data Scientists, and ML Applied Scientists.
• Technical Mentorship: Mentor analytical engineers and data analysts on best practices for scalable data modeling, efficient SQL query design, and quantitative problem-solving.
• Innovation & Emerging Tech: Actively explore, evaluate, and integrate emerging analytics workflow tools and AI capabilities into Faire's data ecosystem.

Requirements

Technical Depth & Analytics Engineering Foundations

• Professional Experience Track: 4+ years of professional experience in analytics and data engineering roles focused on data modeling, large-scale data processing, and tool building for analytics or data science.
• Ads Domain Experience: Direct working experience or strong domain familiarity within digital advertising platforms, ad tech metrics, or monetization analytics is strongly preferred.
• Python Development: Production-level software development experience in Python.
• SQL & Data Modeling: Strong SQL skills with demonstrable competencies designing well-architected data models and optimizing query performance over massive datasets.
• Data Warehousing & Architecture: Deep knowledge of data warehousing concepts, enterprise ETL/ELT pipelines, big data technologies, and modern analytics platforms.
• Analytics Workflow Tooling: Hands-on experience with analytics workflow tools such as dbt, Airflow, Docker, or equivalent technologies.
• Communication & Stakeholder Management: Demonstrated communication and leadership skills, with a history of initiating and steering multi-stakeholder data initiatives to successful completion.
• Educational Background: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related quantitative technical field.

Preferred Qualifications

• Prior experience building data infrastructure for sponsored listings, search ads, or retail media networks (RMN).
• Experience working with machine learning feature stores, real-time ad tracking event streams, or attribution data models.
• Familiarity with Snowflake, Databricks, PySpark, or modern data observability frameworks (e.g., Anomalo, Great Expectations).

Total Rewards & Benefits

• Compensation & Equity: California base salary range ($196,000 – $269,500 USD) + competitive equity grants + comprehensive benefits package.
• Time Off & Workplace Flexibility: Flexible Paid Time Off (PTO), company-wide recharge days, and 4 weeks of remote work flexibility annually for hybrid employees.
• Family & Parental Support: Paid parental leave (up to 16 weeks) alongside comprehensive family-building and fertility benefits through Carrot (including a lifetime reimbursement allowance).
• Health & Mental Wellbeing: Comprehensive medical, dental, and vision insurance coverage, plus mental health support and dedicated coaching through Modern Health.
• Stipends & Retirement: Professional development stipends, wellness allowances, work-from-home setup stipends, and an employer-sponsored retirement plan.