Staff Software Engineer, Streaming

About Judi Health

Judi Health is an enterprise health technology company providing a comprehensive suite of solutions for employers and health plans, including:

• Judi Rx, a public benefit corporation delivering full-service pharmacy benefit management (PBM) solutions to self-insured employers.
• Judi Health™, offering full-service health benefit management solutions to employers, TPAs, and health plans.
• Judi®, the industry’s leading proprietary Enterprise Health Platform (EHP), consolidating all claim administration-related workflows in one scalable, secure platform.

To learn more, visit www.judi.health.

Position Summary

Judi Health is building the technology infrastructure our nation needs to deliver the healthcare we deserve. The Architecture organization is responsible for the technical foundation the rest of the company builds: the standards, patterns, and infrastructure that engineering teams use to move fast and build efficiently. The Realtime & Streaming team sits within Architecture's Core Platform function, owning the streaming infrastructure that services and data consumers depend on for timely, correct event delivery.

Position Responsibilities

Your influence extends beyond what you ship directly. The standards you set, the patterns you establish, and the decisions you document become the reference point for how event-driven systems are built across the organization. The platform's consumers, including cache invalidation systems, analytics pipelines, and change-data-capture subscribers, each carry different latency and ordering requirements. You will be directly responsible for scaling delivery without degrading it while honoring per-consumer SLAs as volume grows to keep historical and real-time data in sync.

Required Qualifications

• 10+ years of production engineering experience, with deep specialization in realtime data infrastructure and event streaming systems.
• Production experience designing and operating WAL-based or log-structured replication systems, such as PostgreSQL logical replication, Debezium, Kafka Connect, or equivalent CDC frameworks at scale with an understanding of delivery guarantees, consumer lag management, and failure recovery.
• Deep understanding of event streaming correctness: ordering guarantees, at-least-once vs. exactly-once delivery semantics, idempotency requirements, and how those properties propagate to downstream consumers.
• Experience leading batch-to-streaming migrations replacing polling or batch-driven synchronization with event-driven architectures without disrupting dependent consumers.
• Fluency in a systems-level language (Rust, Go, or C/C++) used to build high-throughput, low-latency data plane components in production.
• Strong written and verbal communication — you produce architectural guidance that the broader engineering organization depends on.
• Comfortable operating with ambiguity — at this level, you will be handed problems, not plans, and are expected to identify the right approach and drive it from first principles to production.
• Strong experience supporting 24/7 production on-call rotations, including responding to alerts and resolving incidents outside of standard business hours.

Preferred Qualifications

• Systems-level programming experience in Rust for high-throughput streaming pipeline components, such as binary protocol handling, I/O-intensive services, or data plane infrastructure where performance and correctness are both hard constraints.
• Experience with open table formats (Apache Iceberg, Delta Lake, Parquet) as the storage layer bridging streaming ingestion and analytical query workloads.
• Hands-on experience integrating streaming pipelines with analytical query engines — Redshift, Snowflake, BigQuery, ClickhHouse, DataBricks — including schema evolution, backfill strategies, and latency and cost trade-offs.
• Deep familiarity with PostgreSQL WAL internals, including logical decoding, replication slots, checkpointing, and the failure modes that emerge at scale.
• Familiarity with the streaming runtime landscape — Kafka, Kinesis, Redpanda, Pulsar, and similar — and the ability to evaluate trade-offs across managed and self-managed deployment models.
• Experience with AWS data infrastructure and how managed services compose with self-managed streaming components in a hybrid architecture.

Salary Range

• New York, NY: $200,800 USD - $251,000 USD
• Denver, CO: $184,000 USD - $230,000 USD
• Charlotte, NC: $167,200 USD - $209,000 USD

Application Instructions

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