Senior Techincal Leader - Software Engineering | Java/Kafka | Distributed Systems | Spark/Flink | Data Platform | DevOps/SRE | 14+ Years

Meet the Team. Webex Data Analytics Platform (WAP) develops the big data platform that enables teams across Webex to build analytics and data products. We are looking for a hands-on senior technical leader to shape the data platform and software systems built on it, guiding architecture and delivery across data engineering and application development. Your Impact. Set technical direction for scalable data platforms and software systems; turn product needs into architecture, data products, and dependable APIs. Lead Kafka streaming and distributed services for ingestion, enrichment, replication, and asynchronous processing. Lead Spark and/or Flink workloads and manage analytical datasets with Apache Iceberg. Improve performance, reliability, scalability, and cost across workloads. Set engineering standards through architecture and code reviews, prototypes, and technical guidance. Partner across product and engineering teams, mentor engineers, and guide delivery. Minimum Qualifications. 15+ years in either data engineering, software development or cloud engineering for enterprise or large-scale systems. Strong Java, Scala, Python, Go, or equivalent skills; writes maintainable, high-quality code and experience operating/scaling systems in public cloud like AWS, GCP. Strong foundation in algorithms, object-oriented design, service-oriented and microservices architectures, distributed systems and cloud native architecture. Hands-on experience with Kafka and scalable asynchronous systems. Practical experience with Spark and/or Flink, Trino or Presto, and Apache Iceberg. Strong SQL and analytical data modeling skills; tunes systems for scale and reliability. Technical leadership in architecture, reviews, cross-team work, and mentoring. Preferred Qualifications. Experience with real-time stores such as Apache Pinot or ClickHouse. Experience with Spring or Spring Boot and RESTful APIs. Familiarity with Kubernetes, Docker and 12-Factor application principles. Experience with Airflow or DolphinScheduler. Familiarity with DataHub or Apache Amoro. Uses AI development tools such as Copilot, Cursor, or Codex.