Software Engineer, Data Systems

About the role

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.

What you'll do

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

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

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

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

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

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

What you'll bring

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

Compensation range :

The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $230K - $310K plus benefits & equity.

Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above.

If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.