The team owns the data platform layer underneath our core operations.
It builds and operates the real-time data processing systems, quality pipelines, schema infrastructure, and knowledge base tooling that make agent-driven work trustworthy at scale.
What you'll be doing:
Design, build, and operate Flink-based streaming pipelines at production scale, the real-time processing systems at the core of our internal workflows.
Own data quality and observability infrastructure: schema contracts, freshness monitoring, ownership registries, and the alerting systems that catch problems before they affect downstream processes.
Build and evolve the knowledge base tooling that makes institutional context queryable for agents and engineers.
Drive data integrity work: design systems that recover reliably from failure and make the underlying platform trustworthy by default.
Collaborate with the Agentic Data Foundation initiative as we build a company-wide data layer; Data Products is where the proof of concept gets built and validated.
Set technical direction across the team's systems and hold architecture standards with the EM and other Staff engineers.
What you'll need:
8+ years of production backend or data infrastructure experience, with at least 2 years at Staff Engineer or equivalent level
Excellent teamwork and communication skills, with a demonstrated ability to explain complex systems and facilitate collaborative solutions.
Deep experience with stream processing systems (Flink, Kafka, or equivalents) at production scale, including failure modes, recovery, and operational burden.
Strong distributed systems instincts: you think about correctness and reliability before you think about features.
Experience with data quality or observability infrastructure. You've built or owned the systems that keep a data platform honest.
Internal product mindset: you treat the teams you serve as customers and make deliberate choices about what to build vs. what not to build.
It'd be really cool if you also:
Have worked with data contracts, schema registries, or data governance tooling.
Have experience with JVM languages (Scala, Java, Kotlin) and big data DBs (Aerospike/elasticsearch/etc).
Have contributed to agentic or LLM-adjacent infrastructure. You understand what "data quality for agents" actually means in practice.
Have operated at a team technical anchor level in a small, high-scope team where breadth of ownership is the normv.
