Senior Software Engineer - Data Enablement

Block•Bay Area, CA, United States of America, CA

4d•$185,200 - $326,800

About The Position

The Data Enablement team builds platforms and frameworks that move and serve data across Block. It supports online and offline data projections, third-party data integration, and graph data stores for customers including Risk, Compliance, Data Engineering, and Data Science. As a Senior Software Engineer, you will design, build, and operate backend systems that make data easier to acquire, process, and use. Work includes expanding external data acquisition capabilities and contributing to Sessions, which brings customer activity data together for analytics and machine learning. You will help shape technical direction, own projects from design through production, and build shared capabilities for other teams.

Requirements

8+ years of professional software engineering experience, or equivalent experience.
Deep experience designing, building, and operating distributed backend systems in production.
A track record of leading technical projects, making sound architectural decisions, and turning ambiguous problems into well-defined, deliverable work.
Proficiency in a backend programming language such as Java or Kotlin, with strong software design and engineering fundamentals.
Experience building on cloud infrastructure, ideally AWS.
Ability to learn unfamiliar systems and domains, communicate technical trade-offs clearly, and collaborate across software engineering, data engineering, and data science.

Nice To Haves

A data engineering background, including data pipelines, large-scale processing, or lakehouse and warehouse systems.
Hands-on experience with Kafka and Spark Structured Streaming; experience building and operating low-latency streaming systems with Spark Structured Streaming is especially valuable.

Responsibilities

Design and build shared backend services, platforms, and frameworks that support data acquisition, processing, and access across Block.
Lead projects from problem definition and architecture through implementation, rollout, and ongoing production operation.
Work across backend services, event-driven systems, and batch and streaming data processing to deliver reliable capabilities for downstream consumers.
Partner with software engineers, Data Foundations engineers, and data scientists to turn their needs into reusable platform capabilities.
Make practical architectural decisions that balance reliability, latency, scalability, cost, and maintainability.
Improve the observability, data quality, and operational reliability of the systems you build and support.
Mentor engineers, contribute to technical standards, and grow familiar with the team’s other domains over time.