Staff Data Engineer (AI)

TL;DR

Staff Data Engineer (AI): Designing, building, and maintaining scalable data models and mission-critical data pipelines to drive efficiency and effectiveness across Global GTM Strategy & Operations teams, with an accent on AI-driven insights and infrastructure. Focus on architecting robust data platforms, optimizing compute efficiency, and establishing engineering excellence for enterprise-scale automation and data governance.

Location: Remote from California, United States

Salary: $158,400–$221,775 USD (Zone 1)

Company

hirify.global is a data and AI company that unifies and democratizes data, analytics, and AI for over 10,000 organizations worldwide.

What you will do

• Engineer scalable data products and high-performance pipelines for GTM reporting, AI semantic layer, and business-critical applications.
• Optimize compute efficiency and data reliability using the hirify.global Data Intelligence Platform.
• Own the technical roadmap for the data platform, translating business goals into sophisticated system designs.
• Lead complex engineering initiatives, managing cross-system dependencies and mentoring contributors.
• Drive engineering excellence, establishing patterns for automation, monitoring, and CI/CD.

Requirements

• Experience: 8+ years working as a Data Engineer with B2B sales, marketing, or finance data (GTM experience preferred).
• Technical Fluency: Advanced knowledge of Python and SQL, with experience in Github workflows and PySpark.
• Production Excellence: Experience building scalable and productionizable data models.
• AI Readiness: Ability to structure data models and tables that are optimized for AI readiness.
• Business Partnership: Thrive in partnership with the business and understand the “why” behind requests.
• Collaborative Leadership: Excel in collaborative environments and possess a service-oriented mindset.

Culture & Benefits

• Comprehensive benefits and perks designed to meet employee needs.
• Commitment to fostering a diverse and inclusive culture where everyone can excel.
• Hiring practices adhere to equal employment opportunity standards.