Senior Scalability Engineer - Streaming & Realtime Systems

10+ years of software engineering experience with demonstrated progression into technical leadership roles.

3+ years of experience leading technical initiatives, architecting distributed systems, or serving as a subject matter expert on streaming infrastructure.

Strong expertise in Python (Flask/SQLAlchemy) for production applications.

Deep PostgreSQL knowledge: Understanding of write-ahead logs, replication, logical decoding, and change data capture mechanisms.

Production streaming experience: Proven track record building and operating high-throughput streaming systems using Kinesis, Kafka, or similar event streaming platforms.

Distributed systems expertise: Strong understanding of ordering guarantees, exactly-once semantics, partition strategies, backpressure handling, and fault tolerance patterns.

Join our Scalability team as a Senior Scalability Engineer focused on streaming and realtime systems. In this role, you will own the architecture and expansion of our streaming data infrastructure, including WAL-based database replication, change data capture (CDC) systems, and realtime event processing. Your work will handle systems processing hundreds of thousands to millions of records per batch while maintaining strict ordering guarantees and exactly-once semantics. Working closely with our clients and cross-functional teams, you'll build foundational streaming infrastructure while partnering directly with product teams to implement realtime capabilities that power critical business workflows.

In this role, you'll provide technical leadership while delivering hands-on solutions for high-impact performance challenges. You will:

Own streaming infrastructure: Design, implement, and expand WAL-based replication systems that process database changes through Kinesis to Snowflake and Redshift, handling millions of records while maintaining strict ordering and delivery guarantees.

Build CDC systems: Architect and implement change data capture infrastructure for cross-platform data synchronization, enabling realtime analytics and event-driven workflows across the organization.

Develop shared libraries: Create reusable Kinesis/SNS consumer patterns and libraries used across multiple teams, establishing best practices for event processing, error handling, and observability.