Quick overview
Job description
We are looking for a highly technical product owner to own the design, deployment, and operations of our enterprise data streaming platform, with a primary focus on Confluent Kafka infrastructure on Azure and Google Cloud Platform. This is not a traditional product owner role, and it demands deep hands-on expertise in Kafka platform administration, cloud-native Kafka deployments, stream processing infrastructure, and CDC patterns.
- Own the product backlog: decompose epics and business vision into well-defined, developer-ready features and engineering specifications for the streaming platform.
- Expected to deeply understand the "what”, the business intent and streaming use case, and independently derive a very detailed and technical "how”, the infrastructure design, deployment architecture, and engineering specifications ready for the development team.
- Lead the design and buildout of Confluent Kafka infrastructure on Azure and Google Cloud Platform, ensuring enterprise-grade scalability, resilience, and security.
- Define and govern real-time streaming and event-driven architecture patterns adopted across all application and data teams.
- Drive and own ceremonies of SAFe Agile / LPM, including PI planning, iteration planning, backlog refinement, and other ceremonies.
- Must be hands-on technical with the ability to independently write proof-of-concepts (POCs) and reference implementations to guide and accelerate the development team.
- Own Kafka platform administration standards including cluster configuration, topic design, consumer group strategies, schema governance, and data retention policies.
- Build and govern CDC pipelines using Debezium and Kafka Connect, including source and sink connector development and operations.
- Experience building and operationalizing Kafka clusters on Kubernetes using Confluent for Kubernetes, including deployment, scaling, configuration, and day-2 operations
- Experience deploying and configuring Confluent Platform using Ansible playbooks, including cluster provisioning, configuration management, and automated upgrades.
- Define and enforce cloud networking standards for Kafka infrastructure including private networking, and security controls.
- Align cross-functional stakeholders on streaming platform roadmap, architectural tradeoffs, and delivery priorities
- Own capacity management of the streaming platform, including resource planning, scaling strategies, and performance optimization
- Experience with traffic throttling and workload governance using Kafka quotas across producers and consumers
- Experience designing and implementing Kafka disaster recovery patterns, including multi-region replication and failover strategies
- Experience with Confluent Platform Cluster Linking for cross-cluster and cross-region data replication
- Experience building diverse source and sink connector data pipelines using Kafka Connect across a variety of enterprise systems and data stores
- Experience building and managing multi-tenant Flink infrastructure, enabling isolated and secure stream processing workloads across multiple teams and use cases
- Define stream processing infrastructure patterns using Confluent Flink and guide teams in building real-time processing pipelines
Technical Skills Required
Area | Skills |
Kafka Core | Apache Kafka, KRaft, ZooKeeper, Kafka Streams, Kafka Platform Administration |
ConfluentPlatform | Confluent Cloud, Schema Registry, Streaming Gateway, Confluent Flink, Confluentfor Kubernetes, Confluent Operator, Confluent Ansible |
CDC & Connectors | Debezium, Kafka Connect, source & sink connector development and operations |
Stream Processing | Confluent Flink, real-time stream processing infrastructure design and deployment |
Cloud Platforms | Azure, Google Cloud Platform, cloud-native Kafka deployment patterns |
Cloud Networking | Private networking, VNet/VPC peering, private endpoints, security controls for streaming infrastructure |
Data Integration | ETL/ELT streaming patterns, event-driven architecture |
Application Development | REST APIs, Python-based service development |
Agile | SAFe / LPM — PI planning, epic decomposition, backlog ownership |
Desired (Not Required) | IBM StreamSets |
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