Block

Senior Software Engineer, Data Enablement

Rol remoto de 10418 Engineering - Data & Data Science con fit claro de ubicación del candidato.

PublicadoAgregado recientemente

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

Become the subject-matter expert for Block's online data projections and event-streaming capabilities — designing the platform, frameworks, and standards others build on
Lead the technical direction for real-time, event-driven data systems used by business units across Block
Build and operate streaming pipelines and projection frameworks on high-volume event data
Partner with engineering teams across Block to turn Kafka event streams into reliable, low-latency data products
Improve the reliability, observability, and data quality of streaming systems running in production
Mentor engineers on the team and shape platform architecture and standards
Contribute to and grow familiar with the team's other domains over time — supporting our third-party data proxy backend applications, graph data store capabilities, and offline batch data projections

8+ years of professional software engineering experience (or Block equivalent, as referenced in go/levels)
Deep experience designing and operating distributed, high-throughput backend systems in production
Hands-on experience with event-driven architecture and streaming platforms such as Kafka
Experience building streaming or real-time data systems; hands-on experience with Spark Structured Streaming or Flink is strongly preferred
Proficiency in a JVM language such as Kotlin, or a comparable backend or systems programming background
Experience building on cloud infrastructure, ideally AWS
A track record of leading technical projects and mentoring other engineers
Bonus points for a data engineering background (building data pipelines, lakehouse or warehouse modeling, or large-scale batch and streaming systems)