TL;DR

Analytics Data Engineer (AI): Building scalable data pipelines, dashboards, and analytics solutions to provide reliable metrics and insights across the organization with an accent on data integrity, multi-step ETL processes, and cross-functional collaboration. Focus on designing and managing data models, enabling self-serve analytics, and supporting data-driven decision-making in a fast-growing AI company.

Location: Hybrid with at least 25% in-office presence in San Francisco, USA

Salary: $275,000 - $355,000 USD annually

Company

%hirify_global% is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

Collaborate with Engineering, Product, and GTM teams to understand data needs and translate them into technical requirements
Define, build, and manage key data pipelines using dbt and other tools
Ensure high data integrity standards and timely delivery of accurate data
Develop dashboards and data products to track core metrics and enable self-serve analytics
Influence product and GTM roadmaps from a data systems perspective
Become an expert in the company’s data models and architecture

Requirements

Must have 5+ years experience in Analytics Data Engineering or similar roles
Proficiency in SQL, Python, dbt, Airflow, and GitHub
Experience building data reporting and dashboards for cross-functional teams
Bachelor’s degree or equivalent experience
Ability to work in a hybrid setup with at least 25% office presence in San Francisco
English proficiency at least B2 level

Nice to have

Experience building Analytics Data Engineering functions at startups
Passion for AI safety and ethical AI development
Strong initiative and ability to thrive in ambiguity

Culture & Benefits

Competitive compensation including equity and benefits
Generous vacation and parental leave
Flexible working hours and hybrid work policy
Support for visa sponsorship with immigration lawyer assistance
Collaborative and impact-driven research environment