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Lifecycle Operations Manager

Ōura
CompanyŌura
CategoryOperations & Admin
LocationRemote - United States
RemoteRemote
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted22 Jun 2026
Last verified2 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles. Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.  ŌURA is seeking a Lifecycle Operations Manager to serve as the strategic technical and operational anchor of our global lifecycle program. In this role, you will define the technical and operational vision and orchestration framework required to scale our experimentation, personalization, and multi-channel measurement (email, push, in-app, SMS, etc.). You will operate with a high degree of autonomy, bridging the gap between Lifecycle Marketing, Membership Analytics, Data Engineering, and MarTech. You will design the highly scalable, automated foundation that allows our lifecycle marketing team to innovate at speed. What you will do: Systems & Data Foundations Define and own the technical roadmap for our lifecycle tooling ecosystem (e.g., Braze), ensuring total data stability, governance, and future-proof documentation. Lead cross-functional work alongside Lifecycle Marketing, Data Engineering and Data Analytics to define and maintain source of truth lifecycle data models (events, attributes, segments, composite scores, propensity models). Drive operational efficiency by architecting AI-driven automation workflows and internal tooling to eliminate repetitive production overhead (e.g., scalable dynamic content engines).Create and maintain documentation for journeys, data dependencies, and operational workflows. Lead the evaluation and onboarding of new capabilities (e.g., additional channels, new integrations) with a clear view of impact vs. complexity. Journey Orchestration & Execution Collaborate with the lifecycle marketers to systematize journey designs and briefs into robust, testable flows in Braze (or equivalent) Implement and maintain scalable templates, modular components, and reusable logic  Build and manage guardrails and governance for sending rules Partner with lifecycle marketers to ensure new journeys follow best practices  Experimentation &  Measurement Operationalize A/B and multivariate tests end to end, setting up principles for audience configuration, randomization, holdouts, and measurement-ready instrumentation. Collaborate with Lifecycle marketers and Data Science to prioritize and execute personalization experiments and help operationalize outputs into journeys. Collaborate with Analytics to define clear experiment frameworks (success metrics, minimum sample sizes, experiment timelines) and ensure implementation is technically sound. Own reporting requirements for lifecycle ops (e.g., journey health, delivery and error monitoring, experiment status dashboards). Proactively identify opportunities to simplify or consolidate journeys based on performance and operational complexity. Requirements We would love to consider you for this role if you have: 8+ years of deep experience in lifecycle / CRM operations Proven track record of architectural ownership: You have scaled CRM/MarTech platforms (like Braze) for millions of active users, ideally within a subscription or membership-based model. Hands-on experience with a marketing automation platform configuring personalized journeys. Solid understanding of experiment design (control vs test, holdouts, key metrics, avoiding bias), best practices and practical constraints in production systems. D
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