MarTech Manager

Replit•Foster City, CA

1d•Onsite

About The Position

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide and over 500,000 business users, Replit is democratizing software development by removing traditional barriers to application creation. About the role: The MarTech Manager will sit at the intersection of marketing, data, and revenue operations, owning the systems and pipelines that power how we acquire, engage, and convert customers. This role partners closely with Marketing, RevOps, and Data to design, build, and maintain a scalable, reliable marketing technology stack. You’ll be responsible for everything from integrating tools and modeling data to enabling experimentation, attribution, and lifecycle orchestration. This is a hands-on, high-impact role for someone who enjoys both building and problem-solving in a fast-moving environment.

Requirements

6+ years of experience in Marketing Technology, Revenue Operations, Data Engineering, or a related technical role
Strong proficiency in Python and SQL, with experience building and maintaining production data pipelines
Hands-on experience with modern analytics and transformation tools such as dbt and Hex (or similar)
Deep familiarity with Salesforce data models, integrations, and marketing use cases
Experience working with marketing automation and engagement platforms (e.g., Iterable, Marketo, HubSpot, Braze)
Comfort integrating third-party tools and APIs (e.g., Clay or enrichment vendors)
Strong understanding of marketing funnels, lifecycle marketing, and attribution concepts
Ability to work cross-functionally and translate business problems into technical solutions
High attention to data quality, documentation, and system reliability

Responsibilities

Design, build, and maintain integrations across our marketing and revenue tech stack, including Salesforce, Iterable, Clay, and our data warehouse
Own marketing data pipelines using tools like Python, dbt, and Hex to ensure clean, reliable, and well-modeled data
Partner with Marketing to enable lifecycle programs, lead scoring, segmentation, and personalization at scale
Implement and maintain attribution, experimentation, and reporting frameworks that support data-driven decision making
Translate marketing and revenue requirements into technical solutions, balancing speed, scalability, and data integrity
Debug data quality and system issues across tools and proactively improve reliability and observability
Document systems, data models, and workflows to support long-term maintainability and knowledge sharing
Evaluate and recommend new tools or approaches as our go-to-market motion evolves