As a Senior Staff Engineer, Data, you'll be a key technical leader driving the design, implementation, and evolution of FloQast's core data platform. You will define the standards and patterns that power data ingestion, governance, storage, processing, and access across all product and analytics systems — with Apache Spark as the primary compute engine at the heart of that stack. Your work will enable teams across engineering, product, and business operations to build on a reliable, scalable, and secure data foundation.
You've spent years going deep on Spark in production. You reason through shuffle behavior, partition strategies, and memory pressure without reaching for documentation. You understand what the Catalyst optimizer does with your query plan and you write code that helps it. You've made the call between PySpark and Scala Spark on real workloads, run Structured Streaming pipelines over Kafka topics on MSK, and debugged slow stages in the Spark UI. You've built Spark jobs that read and write Apache Iceberg tables at scale — managing snapshot isolation, schema evolution, and compaction as operational concerns, not afterthoughts. At this level, you don't just tune pipelines. You set the architecture that determines whether the next order of magnitude is a rewrite or a config change.
At FloQast, you'll apply that depth across our full lakehouse stack. FloLake runs on Iceberg over S3, orchestrated through MWAA, cataloged in AWS Glue, and queried via Trino and Athena. Kafka on MSK moves data through the hot path. You'll own the compute architecture decisions that 30,000+ tenants depend on, define how Spark jobs are structured and governed across the platform, and set the bar for how the team thinks about distributed systems. Engineers at all levels will look to you as the authority on what good looks like — and you'll build the systems that prove it.