Specialist Solutions Engineer, Confluent

• This role demands expertise in Kafka, distributed systems, and pre-sales engineering, while engaging with cross-functional teams to drive product success and customer outcomes
• Ideal candidates may have backgrounds in Technical Account Management, Sales Engineering, or Professional Services
• Proven experience architecting and implementing enterprise-scale, real-time data streaming solutions with Kafka and related ecosystems
• Deep knowledge of Data Warehouses, Data Lakes, Lakehouses, and Distributed Systems, including CDC Connectors, ETL tools, and RDBMS platforms
• Expertise in distributed data processing, data governance, and real-time analytics
• Hands-on programming experience with Python, Java, or similar, especially for building streaming and ETL pipelines
• A demonstrated ability to become a trusted advisor to Chief Data Officers, Data Engineers, Data Scientists, Data Analysts, and Architects, driving customer success and platform adoption
• Strong pre-sales engineering skills, including technical presentations, proof-of-concept development, and hands-on solution design
• Proven ability to work across cross-functional teams, including product management, engineering, and marketing, to drive shared outcomes
• A passion for learning and adapting to emerging technologies, particularly within the Kafka ecosystem

Desirable

• We’re seeking an innovative and experienced technologist to join our Global Specialist Solutions Engineering team—a group dedicated to solving complex, real-time data challenges and optimizing Data Lake, Data Warehouse, and Data Analytics architectures
• As a trusted technical advisor, you will collaborate closely with product management and engineering, serving as a key advocate for Confluent's platform
• Understand customer challenges with traditional Data Warehouses, Data Lakes, and Batch Analytics workflows, and guide them toward real-time, distributed architectures using Kafka, Flink, Kafka Streams, and modern ETL/ELT frameworks
• Help customers optimize their data platforms by focusing on early-stage data enrichment, filtering, and processing for better performance and cost efficiency
• Assist customers and sales teams in designing, deploying, and optimizing real-time data streaming platforms, integrating Kafka with distributed processing, and ensuring alignment with business goals
• Architect solutions to unify operational and analytical workloads, enabling a data mesh or streaming-first architecture
• Partner with sales, product management, marketing, and engineering to translate customer feedback into continuous improvements for Confluent’s platform
• Work cross-functionally to refine product messaging and technical positioning, ensuring clarity and alignment with customer needs
• Lead technical workshops, webinars, and sessions to showcase the advanced capabilities of Kafka, Kafka Connect, Flink, and other data streaming tools
• Advocate for best practices in real-time architectures through case studies, training sessions, and field engagement with both technical and business stakeholders