Staff Software Engineer (Curated Data)

Join our team as a Staff Software Engineer (Curated Data) and play a key role in building and owning datasets from raw chain data to curated models. You will focus on the lifecycle of building high-quality data, orchestrating interdependent models, and propagating schema changes. This hybrid role requires a backend engineer who thinks in systems and contracts, working on data. You will design and build the control plane for our curated data lifecycle, decide on the architecture for each dataset, and build alerting and data quality signals. You will work across multiple programming languages and break large problems into manageable tasks for other engineers.

• Orchestrate the lifecycle of building high-quality data, including dependency-aware orchestration, backfills, restatements, retries, partial failure, and recovery.
• Design and build the control plane for curated data lifecycle, making decisions on whether the answer is a model, a service, or a job.
• Work across multiple programming languages and tools, choosing the right tool for the job and breaking large problems into manageable work for other engineers.

• You have built or operated stateful stream processing in production (Flink,Kafka Streams, Spark Structured Streaming, RisingWave, Materialize, Feldera)
• You have solid computer science fundamentals and distributed systems understanding
• You communicate clearly in writing and get the best out of a distributed team
• You use AI tools well enough that they have changed how you work, you understand their failure modes and dislike ai-slop
• You have handled schema evolution and data correctness in a system with real consumers downstream, where a breaking change has a cost
• You are a backend engineer who has gone deep on data systems, or a data engineer who became a strong software engineer. You ship production services, not only pipelines
• You debug independently and drive root cause analysis to a fix that holds
• You have built or materially extended orchestration and scheduling systems, and can explain precisely what breaks at scale and why
• You have strong SQL and modeling skills on large datasets, and an interest in how the query engine underneath actually executes your work
• If you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
• Stateful stream processing in production (Flink, Kafka Streams, Spark Structured Streaming)
• Data lake formats such as Parquet, Iceberg or Deltalog
• Experience at a company where the data is the product
• Deep experience with a transformation framework such as dbt or SQLMesh: specifically, having hit its limits and built beyond them