Growth Marketing Manager (Lifecycle Lead)
Kueski Mexico (remote)Est. Est. USD 50,000–75,000 / yearSenior
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Data Science
- Salesforce
- Crm
- Audit
About Kueski
At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for nearly 30% of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.
We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive workplace. Our commitment to excellence and ethical business practices has earned us multiple industry recognitions. In 2024, we were named one of the World’s Top FinTech Companies by CNBC and recognized as one of the most ethical companies
in Mexico by AMITAI. Additionally, we were certified as a Best Place to Work for LGBTQ+ Equality by HRC Equidad MX 2025 and ranked among the Best Companies for Female Talent by EFY.
Position
Kueski is seeking a Growth Marketing Manager for a strategic lifecycle marketer who can take Kueski's CRM to the next level not by sending more, but by sending smarter. You'll own how we engage customers across email, push, SMS, WhatsApp, in-app, and web, with full ownership of the MarTech stack that enables lifecycle execution. This role requires someone who thinks in systems: data-driven journeys, scalable automation, and deep integration between tools and business outcomes. If you're an expert who's frustrated by platforms operating well below their potential and you know how to change that this is your role.
Key Responsabilities
MarTech Strategy & Stack Architecture
Own the lifecycle MarTech stack end-to-end: not just campaign execution, but how platforms are configured, integrated, and evolved to support scalable growth.
Drive the integration between the CRM platform and behavioral analytics tools (e.g., Amplitude, Segment, or equivalent) for real-time audience activation — building dynamic, event-triggered flows, not just pulling reports.
Enable advanced personalization capabilities: real-time API-driven content, in-app and web messaging, and dynamic content powered by live data.
Implement proper measurement infrastructure: conversion tracking tied to business outcomes (loans disbursed, activations, repayments) and control group methodology to measure true incrementality — not just opens and clicks.
Set up user-level preference management to reduce opt-out risk and respect communication preferences at scale.
Lifecycle Architecture & Automation
Design customer journeys powered by dynamic data and database logic — replacing manually-configured, hardcoded flows with scalable, automated systems that minimize operational risk and manual error exposure.
Build a reusable library of journey templates, segmentation frameworks, and content modules that reduce setup time across campaigns.
Define and own the lifecycle strategy across acquisition, activation, engagement, retention, and win-back stages, with clear KPIs at each stage.
Platform Governance & Operational Health
Audit and restructure the current CRM environment: standardize segment architecture, establish naming conventions, and clean up attribute and tag sprawl accumulated over time.
Eliminate dependency on manual data imports by transitioning to event-triggered, API-based audience activation.
Establish governance standards for how campaigns, journeys, and segments are built and maintained — ensuring the platform scales without accumulating technical debt.
Performance & Cross-Functional Collaboration
Own lifecycle KPIs and dashboards; communicate insights with a clear point of view and strategic recommendations, not just raw metrics.
Partner with Product, Data Engineering, and Data Science to improve event tracking, integrate predictive models (churn, upsel
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