Technical Marketing Manager

Confluent
New York, New YorkPosted 27 February 2026

Job Description

Technical Marketing Manager We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them. It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together. One Confluent. One Team. One Data Streaming Platform. ABOUT THE ROLE: We are looking for a Technical Marketing Manager (TMM) with strong software and data engineering foundations to drive adoption and awareness of Confluent among technical audiences — including developers, architects, data engineers, and technical executives. You will turn Apache Kafka, Apache Flink, Apache Iceberg, and Confluent Cloud capabilities into clear, compelling technical stories, demos, and assets that show how Confluent solves real customer problems. You’ll collaborate closely with Product Marketing, Product Management, Engineering, Developer Relations, and the Field to build and scale a world‑class library of technical content and demos. WHAT YOU WILL DO: - Build flagship demos and solutions - Design and implement realistic, reusable demos and reference solutions that showcase Confluent’s Data Streaming Platform (Kafka, Flink, Iceberg, connectors, governance, AI/ML use cases). - Operationalize these demos so they are reproducible, documented, and easy for others to run (field, partners, and customers) - Create technical content that tells a story - Author high‑quality technical content (blogs, whitepapers, reference architectures, lab guides, how‑to videos, webinars) that explains why and how to use Confluent to solve specific problems and use cases. - Translate complex distributed systems concepts into clear narratives that connect architecture to business outcomes. - Partner on launches, campaigns, and use cases - Collaborate with Product Marketing and Product Management on launches and campaigns: define the technical story, proof points, and required assets. - Develop content around priority use cases (e.g., real‑time analytics, app modernization, AI/ML pipelines, data warehouse offload). - Show up as a technical expert in the field - Deliver live and virtual workshops, hands‑on labs, webinars, and conference talks that demonstrate Confluent in action. - Support strategic customer and partner conversations with demos, architectural deep dives, and technical validation. - Drive technical proof and competitive clarity - Build and maintain benchmarks, comparisons, and technical proof points that articulate Confluent’s differentiation vs. alternatives (self‑managed Kafka, CSP‑native services, other stream processing platforms). - Provide input into competitive positioning from a practitioner’s perspective. - Feed insights back into the product - Act as the voice of the practitioner: synthesize feedback from demos, events, customers, and the field to identify product gaps and improvements. - Partner with Product Management to prioritize developer and operator needs on the roadmap. WHAT YOU WILL BRING: - Hands‑on streaming and data experience - 3–5+ years working with streaming/data technologies such as Apache Kafka, Apache Flink, Kafka Streams, Spark Structured Streaming, or similar. - Strong understanding of distributed systems fundamentals and cloud‑native architectures. - Solid software engineering skills - Proficiency in at least one modern programming language (e.g., Java, Python) and comfort writing production‑quality code, samples, and utilities. - Experience with container platforms and orchestration tools such as Kubernetes (K8s) and Docker for deploying and managing applications. - Experience building end‑to‑end applications or data pipelines tha ... (truncated, view full listing at source)