Senior Staff Software Engineer, Data Platform

Coinbase

6h•$253,895 - $298,700•Hybrid

About The Position

Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase. At Coinbase, our mission is to increase economic freedom in the world. Achieving that goal requires not just great products, but a world-class data foundation beneath them. The Data Platform team is the engine that makes Coinbase's data reliable, fast, and accessible at scale — powering everything from fraud detection and financial reporting to the AI and ML systems that will define Coinbase's next decade. We are looking for a visionary, hands-on Senior Staff Software Engineer to help define and lead the technical strategy for Coinbase's Data Platform. This is a foundational role at the intersection of distributed systems, data engineering, and AI-readiness — and a rare opportunity to build something that matters at the infrastructure level of one of the most important companies in crypto. You will report into the Senior Director of Engineering, Data Platform, and serve as the domain's top technical leader. You will set architectural direction, mentor and elevate engineering talent, drive multi-quarter roadmaps, and be a key voice in shaping how Coinbase evolves from a collection of managed data services into a true, scalable data platform. This role operates with significant autonomy and is expected to have impact across multiple cross-functional teams and the broader Infrastructure organization.

Requirements

Deep experience building and operating large-scale distributed data infrastructure — streaming platforms, data lakes, batch and real-time processing engines, and query/serving layers.
Strong systems thinking: you understand the full data lifecycle and can reason about performance, reliability, cost, security and privacy at each layer.
Proven experience moving teams from managed-service dependency toward engineering-built, platform-grade infrastructure.
A platform mindset: You think like a product manager for data infrastructure — deeply empathetic to your developer customers, focused on reducing friction, and obsessed with leverage.
Experience designing data systems that support ML training pipelines, feature stores, real-time inference, or AI agent workloads at scale.
Proven track record owning the technical strategy and architecture for an entire domain across multiple teams.
Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

Nice To Haves

Experience at high-scale tech-forward fintech, crypto, or financial services companies
Familiarity with compliance, data governance, or regulatory data requirements.
Experience with change data capture (CDC), Kafka Connect, or real-time ETL pipelines.
Experience working on Databricks and/or Snowflake
Experience operating large scale data platforms on public cloud infrastructure
Background contributing to open-source data infrastructure projects.

Responsibilities

Define and Drive Technical Strategy: Own the technical strategy and architecture for Data Platform, setting direction across data ingestion, transformation, warehousing, streaming, and serving systems.
Develop and execute a multi-quarter roadmap that transitions the team from operational cost-saving toward engineering-led cost reduction — rethinking how cost scales with infrastructure, not just how to trim it.
Architect for the AI-Native Future: Redesign data infrastructure from the ground up to natively support AI and ML workloads — ensuring that data pipelines, data lake infrastructure, and compute systems can power fraud and other AI models, and modern multi-agent AI architectures.
Drive the evolution to near-real-time data availability: Enable downstream teams to act on fresher data across the company.
Spearhead Builder Mindset: push the team to build data infrastructure that creates compounding leverage.
Drive Cross-Functional Alignment: build alignment and secure commitment from senior leadership and cross-functional partners — product, infrastructure, data engineering, 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.