Backend Engineer (Reporting team) at HockeyStack Inc
San Francisco, California, USA -
Full Time


Start Date

Immediate

Expiry Date

07 Nov, 25

Salary

200000.0

Posted On

10 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

HockeyStack is an Applied AI company on a mission to automate sales, marketing, and customer success for B2B companies. We build the most complete and accurate picture of the B2B buyer by integrating with every tool your team uses, partnering with third-party data providers, and deploying custom AI research agents. We use this data to power applications that automate high-value, high-complexity workflows across the go-to-market and revenue teams. Our core products include:

  • Marketing Intelligence – instantly answers questions like “What led to that sudden drop in pipeline?”
  • Account Intelligence – surfaces next-best actions to help reps move target accounts toward conversion

Since launching in January 2023, we’ve come through Y Combinator, raised a $20M Series A led by Bessemer. We’re growing 3× year-over-year, have hit multimillion ARR, and process over 60 TB of GTM data monthly. Based at our San Francisco HQ, we operate fully in-person, move fast and hire people who are ready to win.

How To Apply:

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Responsibilities
  • Own and continuously improve the backend systems that power all reporting features across the platform
  • Design, write, and maintain high-performance SQL queries — including some that span 500+ lines — to deliver critical GTM insights
  • Develop and maintain backend services in Node.js and Express that transform raw data into actionable output
  • Improve query performance across massive datasets stored in ClickHouse and other systems
  • Work cross-functionally with Product and Frontend teams to deliver accurate, real-time dashboards and insights
  • Implement robust caching strategies, edge-case handling, and reliability measures at scale
  • Ship fast and often — deploying to production frequently while maintaining high-quality standards
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