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Robinhood is seeking a Senior Staff Software Engineer to serve as the technical lead across the Data Platform organization. The Data Platform organization builds and operates the systems that power how data is stored, moved, and consumed across Robinhood, spanning three core pillars: Storage (Postgres, DynamoDB, and caching systems), Streaming (real-time event infrastructure), and Data Lake (ingestion and compute systems built on Delta Lake).
In this role, you will shape architecture and guide execution across multiple teams, working on complex distributed systems challenges such as database sharding and proxy architectures, real-time streaming and CDC systems, and large-scale data ingestion and compute platforms. You'll define and drive key technical bets, partner with engineering leaders to align platform capabilities with business needs, and lead 0→1 initiatives that introduce new capabilities across storage, streaming, and data systems.
Key responsibilities include:
- Lead architectural direction across storage, streaming, and data lake platforms, connecting systems that handle transactional, real-time, and analytical workloads
- Design and guide implementation of distributed systems, including database sharding, proxy-based query routing, and real-time event processing pipelines
- Improve data freshness and latency by evolving streaming and ingestion systems toward near real-time processing goals
- Partner with engineering leaders and teams across Robinhood to define platform strategy, align roadmaps, and ensure systems meet reliability, scalability, and performance requirements
- Drive 0→1 initiatives that introduce new platform capabilities, including next-generation streaming, CDC, and data processing systems
You should bring extensive experience building and scaling distributed systems, with deep expertise in at least two of the following areas: storage systems, streaming platforms, or data lake / large-scale data processing. Strong understanding of database systems such as PostgreSQL and/or DynamoDB, including replication, sharding, and performance optimization is essential. Experience with streaming and event-driven architectures using technologies such as Kafka, Flink, or similar systems, and familiarity with modern data platforms and compute engines such as Spark, Delta Lake, or equivalent large-scale data processing systems are required. You should have a proven ability to lead complex technical initiatives and define technical strategy.
This role is based in the Bellevue, WA office with in-person attendance expected at least 3 days per week.
