Senior Software Engineer - Data Platform

Coinbase is a leading company in the cryptocurrency space dedicated to increasing economic freedom. As a Senior Software Engineer on the Data Platform team, you will build systems that centralize internal and third-party data, enabling teams to access, process, and transform data for analytics and machine learning.

Responsibilities:

• 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

Requirements:

• 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