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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.
Job Responsibility:
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
Requirements:
10+ years of experience as a data engineer or software engineer working on data infrastructure with deep expertise in distributed systems
Expert-level knowledge of event streaming platforms, especially Apache Kafka (producers, consumers, Kafka Connect, stream processing)
Extensive hands-on experience with Snowflake, including performance optimization, cost management, and data modeling at massive scale
Strong understanding of relational databases (particularly Postgres) and experience with CDC patterns and replication strategies in distributed environments
Proven track record architecting and leading major data infrastructure initiatives that handled orders of magnitude growth
Experience establishing data engineering best practices and driving technical strategy across organizations
Strong communication skills and experience influencing technical direction across engineering, analytics, and leadership
Nice to have:
Experience with dbt (data build tool) for transformation workflows
Knowledge of data governance, privacy compliance (GDPR, CCPA), and security best practices
Experience with infrastructure-as-code using Terraform
Background working with high-growth SaaS products at massive scale