Senior Staff Software Engineer, Data Platform

Coinbase is a company focused on increasing economic freedom and is seeking a Senior Staff Software Engineer for their Data Platform team. In this role, you will define and lead the technical strategy for Coinbase's data infrastructure, ensuring it supports various data processing needs and AI workloads.

Responsibilities:

• Own the technical strategy and architecture for Data Platform, setting direction across data ingestion, transformation, warehousing, streaming, and serving systems while driving engineering-led cost reduction at the infrastructure layer
• Architect data infrastructure to natively support AI and ML workloads, ensuring pipelines, data lake systems, and compute can power ML training, feature stores, real-time inference, and multi-agent AI architectures at scale
• Drive the evolution to near-real-time data availability, enabling downstream teams across Coinbase to act on fresher data for fraud detection, financial reporting, and analytics
• Build alignment and secure commitment from senior leadership and cross-functional partners across product, infrastructure, analytics, ML, privacy, security, and compliance on technical priorities and tradeoffs
• Serve as the primary technical voice for Data Platform in org-wide forums including OKR planning, architecture reviews, and long-term infrastructure strategy, while elevating senior engineering talent

Requirements:

• 12+ years building and operating large-scale distributed data infrastructure, including streaming platforms, data lakes, batch and real-time processing engines, and query/serving layers
• Record of owning end-to-end technical strategy and architecture for an entire data domain across multiple teams, with demonstrated success transitioning organizations from managed-service dependency toward platform-grade, engineering-built infrastructure
• Deep systems thinking across the full data lifecycle, with ability to reason about performance, reliability, cost, security, and privacy at each layer
• Demonstrated experience designing data systems that support ML training pipelines, feature stores, real-time inference, or AI agent workloads at scale, with familiarity across technologies such as CDC, Kafka, Databricks, Snowflake
• Platform mindset and product-manager orientation toward data infrastructure, focused on reducing friction for developer customers and creating compounding leverage
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality