Software Engineer, Data Systems

You'll own Gamma's data infrastructure and architecture as we scale to hundreds of millions of users and petabytes of data. This means defining the technical strategy for our end-to-end event pipeline architecture, designing distributed systems that handle massive scale with reliability, and establishing the foundation for how data flows through Gamma. You'll solve the hardest data engineering challenges we face while setting the technical direction for data infrastructure across the company.

As a Staff Data Engineer, you'll balance hands-on engineering with technical leadership. You'll architect solutions for orders of magnitude growth, mentor engineers across the organization, and drive strategic decisions about our data stack. You'll work closely with analytics, product, and engineering leadership to enable data-driven decision making at scale while building systems that serve millions of users and inform critical business decisions.

Our team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.

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  Own and evolve our end-to-end event pipeline architecture, from Kafka ingestion through Snowflake analytics, setting technical direction for data infrastructure

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  Design and architect distributed data systems that scale to orders of magnitude more data volume while maintaining world-class query performance

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  Lead initiatives to build and optimize CDC (change data capture) pipelines and streaming data transformations at massive scale

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  Establish best practices for data quality, pipeline reliability, and system observability across the organization

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  Drive strategic technical decisions about data modeling, infrastructure architecture, and technology choices

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  Mentor engineers and elevate data engineering practices across analytics, product, and engineering teams

• 10+ years as a data or software engineer with deep expertise in distributed systems, data infrastructure, and high-growth SaaS products at massive scale

• Expert-level knowledge of Apache Kafka (producers, consumers, Kafka Connect, stream processing) and event streaming platforms

• Extensive hands-on experience with Snowflake, including performance optimization, cost management, and data modeling; strong foundation in Postgres, CDC patterns, and replication strategies

• Proven track record architecting and leading major data infrastructure initiatives through orders-of-magnitude growth

• Experience establishing best practices and driving technical strategy across organizations

• Strong communication skills with a history of influencing technical direction across engineering, analytics, and leadership

• Proficiency with dbt, Terraform, and working knowledge of data governance, privacy compliance (GDPR, CCPA), and security best practices