Senior Technical Marketing Manager - Confluent

At IBM Global Sales, we bring together innovation, collaboration, and expertise to help clients solve their most complex business challenges. Working across industries and geographies, you'll partner with colleagues, clients, and partners to co-create solutions that drive digital transformation and lasting impact.Success in Global Sales is built on curiosity, empathy, and collaboration. You'll connect technical understanding with strong people skills, building trusted relationships and shaping solutions that improve business and society. With world-class onboarding, continuous learning, and a supportive culture, IBM offers the tools and opportunities to grow your career. Join us and be part of a global team that's passionate about driving innovation and making a difference. With Confluent, an IBM Company, organizations harness continuously flowing data to innovate and win in the modern digital world. We are defining a new category within data infrastructure - Streamhouse - so every organization can build real time experiences and use the power of data in ways that profoundly change how we all live and work. One Confluent. One team. One Data Streaming Platform. Data connects us. About the role We are looking for a Senior 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 help turn bottom-up developer adoption into enterprise growth. You will turn Confluent capabilities into clear, compelling technical stories, demos, and assets that show how Confluent solves real customer problems, including real-time AI and agentic use cases. 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. You will help define and tell the story of Streamhouse, the emerging data architecture category in which applications and AI agents act on fresh, governed, real time business context. 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, security and access control, AI/ML and AI agent 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, such as exactly once semantics and event driven architecture, into clear narratives that connect architecture to business outcomes for audiences from engineers to CTOs and CFOs.
• Develop Streamhouse messaging, reference architectures, and proof points that show how Confluent’s Data Streaming Platform captures, processes, governs, and serves real time context to production applications and AI agents.
• 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, real time AI and AI/ML pipelines, data warehouse offload) and key industries such as financial services and e commerce.
• Measure the impact of your work through adoption, usage, and pipeline influence, and iterate based on what the data shows.
• 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.
• Enable the sales and field teams with technical training, demo kits, and playbooks that help them win deals.
• Represent Confluent in briefings with industry analysts and technical influencers.
• 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).
• Create competitive battlecards and objection handling guidance, and contribute to win/loss analysis, 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.
• Hands on streaming and data experience
• 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, event driven architectures, and cloud native architectures.
• Solid software engineering skills
• Proficiency in at least one modern programming language (e.g., Java, Python) and strong SQL skills, with comfort writing production quality code, samples, and utilities.
• 5+ years of hands on experience with Kubernetes (K8s), plus Docker and other container platforms, for deploying and managing applications.
• Technical storytelling and content skills
• Demonstrated ability to create clear, accurate, and engaging technical content (blogs, talks, demos, labs, docs, or workshops).
• Talent for simplifying complex concepts without losing the important details, for both practitioner and executive audiences.
• Customer and field orientation
• Experience working directly with customers, sales, or solution teams (e.g., as a technical marketer, solutions architect, developer advocate, or sales engineer).
• Comfort gathering requirements, understanding real world constraints, and tailoring solutions and content accordingly.
• Collaboration and ownership
• Track record of end to end ownership: from idea → prototype → content → launch → iteration.
• Ability to work cross functionally across Product, Marketing, Engineering, and Field teams, balancing multiple stakeholders while keeping the practitioner and customer at the center.
• Self directed, comfortable managing multiple workstreams and making decisions without perfect information.
• Deep hands on experience with Confluent Cloud, Confluent Platform, and/or Apache Kafka at scale.
• Experience with Apache Flink (DataStream or Table/SQL APIs) or other stream processing engines in production.
• Familiarity with real time AI, AI agents, and agentic workflows built on streaming data (RAG pipelines, feature streams, context engineering, streaming ETL into vector/warehouse systems).
• Familiarity with open table and lakehouse formats such as Apache Iceberg, Delta Lake, and Apache Paimon.
• Experience creating and delivering hands on workshops (e.g., using Terraform, cloud labs, or self service environments).
• Experience building competitive battlecards or sales enablement that improved win rates.
• Familiarity with the Streamhouse architecture and with building real time context for AI agents and production applications on streaming data.
• Prior experience in Technical Marketing, Developer Relations, or Product Marketing at an infrastructure or data platform company. United States Enterprise Operations Hybrid Professional Multiple Cities RESEARCH TRIANGLE PARK Armonk Raleigh San Jose Austin San Francisco New York (0147) International Business Machines Corporation Apache Apache Kafka Architecture Artificial Intelligence Distributed Systems Docker Engineering Extract, Transform, Load Infrastructure Java Marketing Pipelines Product Marketing Computer Programming Python Structured Query Language Sales Sales Enablement Spark Storytelling Tailoring Technical Marketing Workshops Writing Stream Processing Kubernetes Terraform Datastream Software Engineering Data Platform Streaming Data Apache Flink Kafka Streams Delta Lake Collaboration Apache Iceberg Blogs Confluent Scale