Software Engineer - Data Infrastructure

About the role

The Data Platform team at Figma builds and operates the foundational systems that power analytics, AI/ML, and data-driven decision-making across the company. We serve a diverse set of stakeholders, including AI researchers, machine learning engineers, data scientists, product engineers, and business teams that rely on data for insights and strategy. Our team owns and scales critical platforms such as the Snowflake data warehouse, ML Datalake, orchestration and pipeline infrastructure, and large-scale data ingestion and processing systems, managing all data flowing into and out of these platforms. Despite being a small team, we take on high-scale, high-impact challenges. In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion and reverse ETL capabilities for new product use cases, and strengthening data quality, reliability, and compliance at every layer.

Responsibilities

• Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence across Figma.
• Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company.
• Manage and evolve core platforms like Snowflake, our ML Datalake, orchestration infrastructure, and real-time ingestion systems.
• Improve data reliability, consistency, and compliance, ensuring high-quality data for engineering, research, and business stakeholders.
• Identify and drive cost optimization opportunities across data processing, compute infrastructure, and storage.
• Collaborate with AI researchers, data scientists, product engineers, and business teams to understand data needs and build scalable solutions.
• Drive technical decisions and best practices for data ingestion, orchestration, processing, and storage.
• Mentor and support engineers, fostering a culture of learning and technical excellence.

Requirements

• 5+ years of backend or infrastructure engineering experience, including designing and building distributed data infrastructure at scale.
• Strong expertise in batch and streaming data processing technologies such as Spark, Flink, Kafka, or Airflow/Dagster.
• Proven track record of impact-driven problem-solving in fast-paced environments, with a strong focus on high-quality, reliable, and performant systems.
• Excellent technical communication skills, with experience collaborating across both technical and non-technical stakeholders.
• Experience mentoring engineers and fostering a culture of learning and technical excellence.

Preferred qualifications

• Familiarity with our stack, including Golang, Python, SQL, frameworks such as dbt, and technologies like Spark, Kafka, Snowflake, and Dagster.
• Experience building data infrastructure for AI/ML pipelines, including model serving, feature stores, or dataset compliance.
• Experience with reverse ETL, personalization platforms, or real-time event ingestion systems.
• Experience with data governance, access control, and cost optimization strategies for large-scale data platforms.
• The ability to navigate ambiguity, take ownership, and drive projects from inception to execution.

Pay & benefits

• Annual base salary range: $153,000—$376,000 USD
• Equity offered to employees
• Health, dental, and vision coverage
• Retirement benefits with company contributions
• Parental leave and reproductive or family planning support
• Mental health and wellness benefits
• Paid time off (flexible PTO for exempt employees, plus paid sick leave, holidays, and other leave benefits)
• Company recharge days
• Cell phone and home internet reimbursements
• Lifestyle spending accounts
• Annual bonus plan for eligible non-sales roles; sales incentive compensation for most sales roles

Schedule

This is a full-time role that can be held from one of our US hubs or remotely in the United States.