Staff Software Engineer - Streaming

Databricks•Seattle, WA

7d•$182,400 - $247,000

About The Position

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can turn deep data insights into better business outcomes. We are the Spark Structured Streaming team, responsible for building stream processing into Apache Spark and the Databricks Data Intelligence Platform. Stream processing is still in its early days, and we're here to build not only state-of-the-art streaming technology but also a best-in-class managed offering for customers to run their streaming workloads. We're seeking an experienced Staff Engineer to drive the technical direction of Spark Structured Streaming, spanning both open source and Databricks-specific components. Your mission is to make Spark Structured Streaming the state-of-the-art stream processing engine — adding advanced capabilities such as sophisticated state management and new operators, while re-imagining the engine's architecture to drive improvements for latency, throughput, and cost.

Requirements

BS (or higher) in Computer Science or a related technical field, or equivalent practical experience
8+ years building related systems — big-data ecosystems, Apache Spark, or database internals
A passion for database systems, storage systems, distributed systems, language design, or performance optimization
Comfortable working toward a multi-year vision with incremental deliverables
A track record of delivering features while maintaining a high bar for operational excellence and engineering quality
Comfortable working cross-functionally with product management and directly with customers, with the ability to deeply understand the product and customer personas

Responsibilities

Set and drive the technical vision for Spark Structured Streaming across OSS and the Databricks Data Intelligence Platform
Design and build core engine capabilities — state management, new operators, and architectural improvements to latency and throughput
Raise the bar for engineering quality and operability, building software that is not just high quality but easy to run in production
Make company-wide impact by driving stream processing adoption across the Databricks product portfolio
Guide long-term architecture and technical-debt decisions, balancing them against the product roadmap
Mentor and technically lead engineers on the team, and partner with the Engineering Manager to attract and grow top-tier talent