Senior Software Engineer, Data Infrastructure

Own and Scale Core Platform Components: Take responsibility for the design, architecture, and implementation of 1–2 key data platform frameworks within our stack

Collaborate and Align: Partner with infra, data science, and product engineering teams to ensure your target platform's capabilities are directly guided by platform governance and product requirements.

Optimize Performance at Scale: Dive deep into engine internals, query planning, state management, memory optimization, serialization efficiency to maximize throughput and reliability under heavy load.

Drive Infrastructure Robustness: Lead the design, testing, and operational lifecycle of next-generation infrastructure features running on Kubernetes across cloud environments.

Agentic Interface: Embed AI/ML capabilities within our data platforms, leveraging LLMs for data discovery and generation, building autonomous, self-serve mechanisms for platform interaction layer.

5+ years of experience building, designing, testing and maintaining production-grade, large-scale distributed systems.

Data Platform Depth: Deep technical experience building or strong familiarity with at least 1 or 2 foundational technologies within our stack: Kafka, Flink, Spark, Trino, Druid, Airflow, or Data Catalog/Metadata systems.

Strong Engineering Foundations: Robust proficiency in Java, Go, or Scala, with a track record of writing clean, highly performant backend code.

Cloud Fluency: Experience operating and troubleshooting data infrastructure at scale on top of Kubernetes in AWS or GCP.

Technical Leadership: Demonstrated ability to influence technical direction across teams, mentor engineers, and drive alignment on complex cross-cutting initiatives.

B.S. equivalent in CS or sufficient experience.