Senior Analytics Engineer: AI-Powered Data & Pipelines Lead

Faire Wholesale Inc.; San Francisco (CA); Hybrid; USD 196,000 - 270,000; Full time

Benefits offered by this job

Equity

Benefits

Hybrid work

Job summary

Faire is seeking a technical leader to work closely with Data Scientists, Product Analysts and Software Engineers to design and build 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.

Qualifications

• 4+ years in analytics & data engineering with data modeling and large-scale processing
• Strong SQL with well-architected data models and optimized queries
• Experience with data warehousing, ETLs, big data technologies, and analytics platforms
• Experience with Airflow, Docker, DBT or similar analytics workflow tools
• BA/BS in Computer Science, Math, Physics, or a related technical field

Responsibilities

• Lead cross-team and/or multi-phase projects from design through implementation.
• Build scalable data models and pipelines aligned with architecture, domain requirements, and roadmap.
• Establish data quality, validation, testing, and observability practices.
• Embed AI into daily data workflows and streamline pipeline development.
• Collaborate with Data Scientists, Product Analysts and Software Engineers to support product launches.

Skills

Data modeling

SQL

Data warehousing

ETL

Airflow

Docker

DBT

Big data

Analytics platforms

Leadership

Communication

Education

BA/BS in Computer Science, Math, Physics, or related field

Tools

Airflow

Docker

DBT

Job description

Faire is seeking a technical leader to work closely with Data Scientists, Product Analysts and Software Engineers to design and build 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.