Engineering Manager, Growth

Sentry•San Francisco, CA

13d•$220,000 - $450,000

About The Position

Sentry is looking for an Engineering Manager to lead their Growth team, internally called "Value Discovery." This role is crucial for expanding Sentry's product-led business by helping customers discover and maximize the value they get from the platform. The team's approach to growth is customer-centric, prioritizing customer value over conversion pressure, and always putting the customer first in any business vs. customer tradeoff. The manager will collaborate with Product, BizOps, Data, Design, and GTM teams to identify opportunities for delivering more value to developers and ensuring these improvements are data-supported. This is a new role, and the manager will have significant ownership in defining and executing the roadmap in partnership with design and data teams.

Requirements

3+ years managing engineers, including experience owning a metric-driven team.
Strong engineering background.
Technically credible with senior engineers, able to engage substantively in architecture and technical decisions.
Strong product sense; ability to identify where a change will create the most value.
Experience helping users get the most out of a complex product.
Working fluency with experimentation frameworks, feature flags, A/B testing, and analytics instrumentation.
Able to talk to users credibly about their workflows, tooling, and pain points.

Nice To Haves

Experience working on growth at a developer tools company.
Experience building experimentation infrastructure from a low starting point.
Experience running experiments at volumes where significance wasn't guaranteed.

Responsibilities

Lead a team of engineers, set priorities, and be accountable for the metrics the team moves.
Define and execute the roadmap for Sentry's self-serve funnel, including signup and onboarding, first-run activation moments, trial and upgrade paths, and pricing and billing surfaces.
Evolve experimentation foundations, including flagging, instrumentation, and readouts, in partnership with the Data team.
Run a fast, disciplined experimentation loop where hypotheses are argued before they are built.
Hold conversion and activation metrics alongside churn, support volume, and 90-day retention, and report on all of them, including experiments that yield flat results.
Grow the engineers on the team, including the skill of doing excellent work on features that might be deleted later.