Engineering Manager (Growth)

Role Overview

Engineering Manager (Growth) to lead Fleetio’s Growth Engineering squads and build high-performing engineering teams focused on product-led growth, experimentation, and data-driven decision making.

Responsibilities

• Lead and develop high-performing engineering teams owning initiatives across the customer journey: activation, adoption, and monetization.
• Optimize engineering execution and foster a high-quality, accountable engineering culture.
• Partner with Product, Design, Data, and Engineering leadership to shape strategy and identify high-leverage opportunities.
• Ensure teams run high-quality experiments and translate learnings into product direction.
• Manage and coach direct reports, helping engineers grow into exceptional growth engineers.
• Create systems that improve engineering velocity without sacrificing maintainability, reliability, or customer experience.

Requirements

• Direct experience managing engineering teams running structured growth and experimentation programs.
• Strong background in experimentation, analytics, and event instrumentation plus product development.
• Ability to balance speed with engineering excellence and customer experience.
• Strong data fluency to challenge assumptions, reason about statistical fundamentals, and coach engineers to produce trustworthy data.
• Hands-on familiarity with usage/event analytics tooling such as Snowflake and Segment, and experimentation/product analytics platforms such as GrowthBook (or similar).
• Understanding that experimentation goes beyond A/B tests (fast learning loops, high-quality decisions, continuous customer experience improvement).
• Proven engineering leadership and people management: setting clear expectations, sustaining engagement, and delivering measurable outcomes.
• Excellent written and verbal communication; ability to align multiple stakeholders.
• Experience leading growth-focused engineering organizations in a B2B SaaS environment.

Nice to Have

• Experience with experimentation platforms and program operations including guardrail metrics, statistical significance, experiment analysis, and translating results into product strategy.
• Experience optimizing key metrics such as onboarding, activation, engagement, retention, monetization, or conversion optimization.