Senior Data Engineer

Role overview Build and operate the data platform that turns high-volume auction events into reliable, timely information for customers and internal teams. You will take ownership of streaming ingestion, storage, transformation, and reporting infrastructure, working with engineering, analytics, and business colleagues as the platform scales. The role also includes incident response through a global on-call rotation.

Responsibilities - Own event data flow from collection through queryable storage, including throughput, cost, schema changes, partitioning, retention, and health instrumentation. - Choose and implement scheduling and transformation tools, then develop tested datasets, aggregates, and materialized views with lineage and backfill support. - Build data services that meet freshness and latency expectations for customer-facing reporting and support self-service analysis across teams. - Establish freshness, reconciliation, and quality checks so late or incorrect data is detected early. - Participate in on-call, investigate platform incidents, and improve reliability based on what you learn. - Document data definitions and communicate platform behavior to technical and non-technical stakeholders.

Requirements - Hands-on ownership of ingestion, storage, and scheduling for a production data platform with real downstream users. - Production experience with high-throughput streaming or queueing systems, including challenges such as partitioning, lag, duplicate delivery, backpressure, and replay. - Experience with columnar data stores and large event datasets; the role particularly values experience operating ClickHouse at scale. - Strong coding skills and continued interest in hands-on delivery, including leading larger projects collaboratively. - Clear written communication and the ability to explain complex technical concepts and data meaning. - Good judgment in an early-stage environment, balancing delivery speed with rigor and reliability.

Nice to have - Experience with AWS, Kubernetes, Postgres, Golang, and observability tools such as Datadog. The storage-adjacent scheduling and transformation choices are open to the engineer's recommendations.

Benefits and work setup The team works remotely with flexible hours and limited synchronous meetings; a global follow-the-sun on-call rotation is used. Benefits include equity, medical, dental, and vision coverage, plus a hardware budget. The stated US base salary range is $150,000–$300,000.