Lifecycle Operations Manager

Oura Oura · Consumer · United States · Remote · Marketing

The Lifecycle Operations Manager will be the strategic technical and operational anchor for Oura's global lifecycle program, focusing on scaling experimentation, personalization, and multi-channel measurement. This role involves defining the technical roadmap for lifecycle tooling, ensuring data stability, and architecting AI-driven automation workflows to enhance operational efficiency and enable the lifecycle marketing team to innovate at speed. The manager will also oversee journey orchestration, execution, and the operationalization of A/B tests and personalization experiments.

What you'd actually do

  1. Define and own the technical roadmap for our lifecycle tooling ecosystem (e.g., Braze), ensuring total data stability, governance, and future-proof documentation.
  2. 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).
  3. 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.
  4. Lead the evaluation and onboarding of new capabilities (e.g., additional channels, new integrations) with a clear view of impact vs. complexity.
  5. Collaborate with the lifecycle marketers to systematize journey designs and briefs into robust, testable flows in Braze (or equivalent)

Skills

Required

  • 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.
  • Demonstrated experience partnering with data and engineering teams on integrations, advanced data models, and troubleshooting.
  • Proven ability to manage multiple initiatives and cross function partners in parallel with clear prioritization and communication.
  • Excellent problem‑solving and debugging skills; comfortable owning issues end to end until resolved.
  • Technical proficiency with HTML and templating logic (e.g., Liquid or similar); comfortable reading, writing, and debugging dynamic content and personalization rules.

What the JD emphasized

  • AI-driven automation workflows
  • propensity models
  • personalization experiments
  • architectural ownership
  • scaled CRM/MarTech platforms for millions of active users