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The Growth Engineering team’s mission is to drive sustained usage and revenue growth by building platform-level campaign intelligence, governance, and personalization systems. We enable growth teams to move from guesswork to action by delivering high-quality data, deep diagnostics, and flexible campaign management across the full campaign lifecycle. The team owns the core technology (Iris) for campaign insights, campaign governance, experimentation, and growth decisioning. Our platforms power Iris Insights, Iris campaign management, campaign performance and governance capabilities that balance growth velocity with customer experience at scale.
Job Responsibility:
Lead a team of full-stack engineers building growth intelligence and campaign management platforms
Own the end-to-end technical architecture for campaign insights, diagnostics, and governance systems
Drive high engineering quality through architecture reviews, design reviews, and code reviews
Build platforms that provide clear, actionable visibility into campaign performance
Enable self-serve diagnostics and insights
Partner closely with product management and data analysts
Design and evolve platform-level mechanisms that protect customer experience while enabling growth
Ensure systems provide cross-campaign and cross-surface visibility
Own feature execution and rollout plans
Collaborate with engineering peers across orgs and geographies
Influence org-wide technical direction and contribute to shared platform standards
Mentor and grow senior engineers and EMs
Foster a culture of ownership, systems thinking, and growth mindset
Drive org-level initiatives that improve execution rigor, engineering excellence, and collaboration
Requirements:
14+ years of hands-on product development experience
5+ years of experience leading engineering teams (up to ~10 engineers), including senior engineers
Proven experience delivering large-scale, cross-team platforms with measurable business impact
Strong understanding of backend and frontend (web) systems
Experience designing and operating data-intensive systems, including analytics pipelines, aggregations, and reporting layers
Big data experience (preferred), especially in systems that support experimentation, funnels, and attribution
Ability to make sound architectural decisions balancing scale, performance, and extensibility
Familiarity with digital marketing, growth platforms, or experimentation systems is a strong plus
Strong problem-solving skills with the ability to think systemically and strategically
Track record of delivering results through influence, collaboration, and technical leadership
Experience working across teams, orgs, and geographies