Principal Engineer - Data Governance & Streaming

Confluent; United States; On-site; USD 285,000 - 342,000; Full time

Job summary

Confluent is seeking a Principal Engineer to shape the long-term architecture, scalability, and reliability of the schema, metadata governance, and policy enforcement within the Data Streaming Platform.

You will own company-level domains, drive critical initiatives, and influence engineering practices and product strategy with autonomy in ambiguous spaces to ensure reliability and growth at scale.

Qualifications

• Leading architecture and delivery of large-scale distributed systems.
• Knowledge of fault tolerance, consistency, and cloud-native platforms.
• Experience with streaming architectures, data catalogs, or metadata/governance systems.
• Ability to influence executives and stakeholders amid ambiguity.
• Proven track record delivering shipped, adopted outcomes.

Responsibilities

• Define and drive company-level technical strategy for governance systems.
• Architect metadata management systems with low-latency lookups and strong consistency.
• Design data protection capabilities including encryption and access control.
• Build highly available, multi-tenant infrastructure for governance services.
• Establish engineering standards and architectural patterns across the org.
• Collaborate across teams to align technical vision with business goals.
• Mentor senior staff and contribute to open-source initiatives.
• Contribute to external representation through talks and thought leadership.

Skills

Technical leadership

Distributed systems

Streaming architectures

Strategic influence

Executive communication

Delivery execution

Job description

Confluent is seeking a Principal Engineer to shape the long-term architecture, scalability, and reliability of the schema, metadata governance, and policy enforcement within the Data Streaming Platform.

You will own company-level domains, drive critical initiatives, and influence engineering practices and product strategy with autonomy in ambiguous spaces to ensure reliability and growth at scale.