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Salary: USD 153,000 - 376,000 / annual
Figma is seeking a Data Platform Engineer to join its Data Engineering team and help build foundational systems powering Figma's next generation of AI-driven products and data experiences. This is an early-stage opportunity to shape Figma's ML and data platform, working at the intersection of data, infrastructure, and machine learning.
You will build and evolve the shared data platform that powers analytics, Data Science, and data-driven product development across Figma. Key responsibilities include:
• Build and evolve the shared data platform powering analytics, Data Science, and data-driven product development
• Improve data development velocity by enhancing local development, testing, CI/CD, staging, and deployment workflows
• Create self-service tools and clear paths for teams to build, deploy, and operate reliable data pipelines
• Improve reliability of critical data systems through better monitoring, data quality, incident response, upgrades, and performance management
• Make trusted data easier to find and use by establishing clear definitions, ownership, lineage, and reliability expectations
• Partner across Data Engineering, Data Infrastructure, Data Science, Research, Modeling Platform, Security, and Product Engineering to define ownership boundaries and supported patterns for batch, micro-batch, reverse ETL, and product-facing delivery
This is a full-time role available from Figma's US hubs (San Francisco or New York) or remotely within the United States.
REQUIREMENTS:
• 5+ years of experience building and operating production data platforms, developer infrastructure, or distributed systems
• Strong software engineering skills (Python or similar), with experience designing reliable and scalable systems
• Experience improving developer workflows such as local development, testing, CI/CD, orchestration, or deployment
• Experience with modern data infrastructure, such as cloud data warehouses, transformation frameworks, workflow orchestrators, infrastructure as code, and observability tools
• Track record of owning shared systems end to end, leading ambiguous cross-functional projects, and communicating effectively with Data Science, Infrastructure, and Product Engineering partners
PLUS (not required):
• Experience supporting ML or research data workflows
