Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.
Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.
With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in
Deloitte’s Fast 500
(four years running!),
LinkedIn’s Top Startups
,
Forbes’ Cloud 100
(five years running!),
Inc.’s Best Workplaces
, and the
Human Rights Campaign Foundation's Corporate Equality Index
!
- Build robust, executive-facing dashboards to support key business and operational decisions across the organization
- Design, build, and maintain scalable data models, semantic layers, and reporting datasets using dbt, Looker, SQL, and related tools
- Use data modeling, statistics, and other analytical techniques to extract and analyze data from large datasets, identifying trends, patterns, and anomalies to drive insights
- Develop and manage our data analytics platform Looker
- Own end-to-end delivery of analytic engineering initiatives across functional domains, from requirements gathering through implementation, proactively managing timelines, dependencies, and stakeholder communication
- Partner with product, engineering, business intelligence, finance, operations, and other stakeholders to define metrics, analytics requirements, reporting solutions, and data quality expectations
- Identify and resolve data quality issues by implementing validation checks, improving data reliability, and driving enhancements to analytics processes and tooling
- Create and maintain documentation for metrics, data models, dashboards, business logic, and analytics workflows to improve consistency and usability across teams
- Provide mentorship and actionable feedback to junior analytics engineers, contribute to code reviews, and improve team standards to elevate overall analytics quality and consistency.
