Lead Engineer, AI Engineer (Applied​/Software), Data Engineering

Overview

Lead Engineer Marketing Technology

Role Summary Catalyst Brands is seeking a Lead Engineer, Marketing Technology to design, build, and scale the next generation of customer engagement, loyalty, personalization, and marketing activation capabilities across our portfolio of iconic retail brands.

This role sits at the intersection of engineering, customer data, marketing technology, and AI. You will lead the development of cloud-native solutions that enable Customer 360, Cross-Brand Loyalty, audience activation, real-time personalization, and data-driven marketing programs. Working closely with Product, Marketing, Data & Analytics, Architecture, and Platform Engineering teams, you will deliver scalable solutions that unlock customer insights and drive meaningful business outcomes.

The ideal candidate is a hands-on engineer with deep expertise in marketing technology ecosystems, customer data flows, event-driven architecture, and modern cloud platforms. You are passionate about building platforms that transform customer experiences while maintaining the highest standards of performance, scalability, and reliability.

Key Responsibilities Build and Scale Marketing Technology Platforms

• Design, develop, and support enterprise-scale Marketing Technology solutions across Customer Data Platforms, Loyalty Platforms, CRM systems, Personalization Engines, and Marketing Activation platforms.
• Develop scalable APIs, microservices, and integrations that enable seamless customer data exchange across enterprise systems.
• Build reusable services and capabilities that support audience segmentation, customer profile management, and campaign activation.

Develop Real-Time Customer Data Solutions

• Design and implement event-driven architectures leveraging Kafka to support real-time customer engagement, identity resolution, personalization, and marketing activation.
• Build highly scalable customer data pipelines that process customer interactions across digital, loyalty, store, and marketing channels.
• Partner with Data Engineering teams to ensure data quality, governance, and customer data availability across the ecosystem.

Cloud Engineering and Platform Modernization

• Design and deploy secure, scalable, and resilient solutions on AWS.
• Utilize AWS services to support customer data management, application integration, event streaming, analytics, and AI-driven marketing capabilities.
• Drive modernization initiatives that reduce technical debt and improve platform agility.

Enable Customer-Centric Experiences

• Partner with Marketing, Product, Analytics, and Business stakeholders to deliver personalization, customer engagement, and loyalty capabilities.
• Support Customer 360 and Cross-Brand Loyalty initiatives by integrating customer data across internal and third-party platforms.
• Translate business requirements into scalable technical solutions aligned with enterprise architecture standards.

AI and Innovation

• Identify opportunities to leverage AI and machine learning capabilities to improve customer experiences, audience targeting, campaign effectiveness, and marketing operations.
• Support implementation of AI-enabled capabilities across the Mar Tech ecosystem.
• Evaluate emerging technologies and establish reusable patterns that accelerate innovation.

Engineering Leadership

• Lead technical design reviews and contribute to platform architecture decisions.
• Mentor engineers through code reviews, technical guidance, and best-practice adoption.
• Champion software engineering excellence through CI/CD, automated testing, observability, Dev Sec Ops , and infrastructure-as-code practices.
• Foster a culture of collaboration, ownership, innovation, and continuous improvement.

Qualifications – Experience & Capabilities

• Experience with Epsilon customer data, identity, marketing activation, or data onboarding solutions.
• Familiarity with Loyalty Platforms, Marketing Automation Platforms, Customer Journey Orchestration tools, and CRM ecosystems.
• Experience with Snowflake, Databricks, Redshift, or modern cloud-based analytics platforms.
• Experience implementing AI and machine learning capabilities within customer experience or marketing technology solutions.
• Retail,…