What You'll Do

Build and maintain real-time data pipelines that ingest market events across our platform with high reliability and low latency
Investigate and resolve root causes of data gaps, delivery delays, and schema breaks before they compound into larger incidents
Ship incremental improvements to ingestion and delivery infrastructure on a continuous basis — not just when something breaks
Monitor pipeline health, define meaningful alerts, and reduce the operational overhead of keeping systems running
Partner with analysts and engineers to understand how data is consumed downstream and improve the quality and shape of what gets delivered
Document systems clearly enough that any engineer on the team can context-switch into your systems without friction

What We're Looking For

5+ years of experience building and operating production data pipelines with real throughput and real consequences when they fail
Strong proficiency in Python or a similar language for pipeline development, data transformation, and tooling
Hands-on experience with stream processing systems such as Kafka, Flink, or Kinesis in a production environment
Track record of debugging hard data reliability issues — schema drift, late-arriving events, ordering anomalies — and getting to root cause without a lot of hand-holding
Comfort operating in resource-constrained environments where you own the full lifecycle of what you build, from design through ongoing maintenance
Experience working with cloud data infrastructure, particularly on AWS or GCP, including storage, compute, and orchestration tooling
(Plus) Experience in financial markets, crypto infrastructure, or other latency-sensitive trading environments
(Plus) Familiarity with blockchain event indexing or on-chain data ingestion
(Plus) Experience building or maintaining data contracts and schema registries across multiple producers and consumers