Engineering Manager - Cc Ui Apps (kafka, Governance, and Tableflow)

Confluent Confluent · Data AI · ON +1 · Remote · Engineering

This role is for an Engineering Manager at Confluent, leading teams that build UI applications for Kafka, Tableflow, and Governance. The focus is on creating user experiences for data engineers and platform operators to manage streaming data, including features like stream governance, schema management, and catalog search. The role involves technical leadership in architecture and backend contracts, as well as people management, hiring, coaching, and scaling the team. While the company works with data streaming platforms and governance, the core of this specific role is in building user-facing applications and managing engineering teams, not directly in AI/ML model development or research.

What you'd actually do

  1. Own the overall vision and execution for Kafka UI, Tableflow UI, and Governance UI — including, but not limited to, Data Portal, Governance-aware Kafka experiences, and Tableflow integrations in lineage and catalog — to deliver cohesive, intuitive user journeys for data engineers, platform operators, and governance stakeholders in Confluent Cloud.
  2. Work closely with product management, design, and TPMs to build and drive the roadmap for these experiences, enabling seamless adoption and operation of capabilities like stream governance, schema management, catalog search and discovery, and Tableflow, while balancing net‑new features with migrations, deprecations, and UX improvements.
  3. Partner with backend and platform teams (e.g., Kafka, Schema Registry, Data Catalog/RBAC, Search, Tableflow/Unified Storage, Observability) to define clear API contracts and sequencing, de‑risk cross-team dependencies, and ensure UI flows remain robust as services evolve (including upgrades to new APIs and retirement of deprecated ones).
  4. Raise the operational bar for this team by instilling strong execution practices — including effective retrospectives, clear ownership and accountability, and a predictable approach to managing capacity across “big rocks” and papercuts — while giving the team room to choose the day‑to‑day execution model that works best (e.g., sprints vs. Kanban).
  5. Build, grow, and lead a team of engineers working on cloud UI applications: hire and retain top talent, provide coaching and feedback, create structured onboarding in a complex domain (Kafka, governance, catalog, Tableflow), and develop engineers into senior technical and leadership roles.

Skills

Required

  • software development experience
  • engineering management experience
  • leading teams that deliver complex, customer-facing cloud experiences
  • Kafka, data streaming platforms, or data governance/catalog products
  • shipping features that sit on top of such systems
  • large scale systems engineering or distributed systems
  • building or integrating with cloud-native services
  • APIs powering search, catalog, permissions/RBAC, governance workflows, or storage/table systems
  • driving execution across multiple concurrent initiatives
  • net-new feature development
  • operational work like API migrations, deprecation-driven changes, quality improvements, and papercuts
  • maintaining clear priorities and predictable delivery
  • influence and align cross-functional partners
  • clear communication
  • structured status and risk narratives
  • data-informed decision making
  • hiring while maintaining a high talent bar
  • keeping engineers engaged and motivated
  • providing effective coaching and feedback
  • handling performance management in a fair and transparent way
  • governance and platform UX
  • catalog or lineage UIs
  • schema lifecycle workflows
  • table/warehouse integrations such as Tableflow, Iceberg, or similar
  • cloud environment

Nice to have

  • BS Degree in Computer Science, Engineering, or equivalent experience
  • advanced degree in computer science or a related discipline

What the JD emphasized

  • 8+ years of software development experience
  • 3+ years of engineering management experience
  • Kafka, data streaming platforms, or data governance/catalog products
  • large scale systems engineering or distributed systems
  • governance and platform UX