Senior Software Engineer - Data Platform

Title: Senior Software Engineer - Data Platform Location: Remote - USA

As a Senior Software Engineer on the Data Platform team within the Platform group, you will help build the systems that centralize all of Coinbase's internal and third-party data. The Data Platform team makes it easy for teams across the company to access, process, and transform data for analytics, machine learning, and powering end-user experiences. You'll contribute to the full spectrum of our systems, from foundational data storage and processing to scalable pipelines, frameworks, and internal applications that make data efficiently available to every team at Coinbase.

What you'll do:

• Own the design, development, and operation of foundational data services spanning cloud data warehouses, data lakes, orchestration (Airflow), batch processing (Spark, SQL), streaming (Kafka), query federation, and real-time event aggregation stores.
• Build and maintain data integration and processing SDKs used by internal services and product teams throughout Coinbase to interact with the data platform reliably at scale.
• Deliver self-service applications that empower users to manage, monitor, and troubleshoot their own data pipelines running on our platform infrastructure.
• Architect end-to-end data security and observability services, including access controls across multiple storage and access layers, data quality tracking, dataset cataloging, lineage, and usage auditing.
• Partner with data analysts, ML engineers, and security and compliance teams to convert functional requests into reusable, scalable patterns and assemble data microservices into platforms for critical business verticals.

Required Skills and Experience:

• 5+ years of experience in backend software engineering, with hands-on experience building and operating data systems or data pipelines in production.
• Proficiency in Python, Go, or Java for backend development, with demonstrated ability to build services that process and serve data at scale.
• Experience with data infrastructure patterns including scale-out architectures, caching layers, key/value stores, and columnar storage systems.
• Hands-on experience with SQL, Airflow, Spark, Kafka, or similar data processing and orchestration frameworks in production environments.
• Experience with data security, access control, or data observability systems, including cataloging, lineage, or quality monitoring.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.