[Hiring] Software Engineer, Data Infrastructure @Figma

Role Description

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. 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.

• 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.

Qualifications

• 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.

Requirements

• 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.

Benefits

• Equity to employees.
• Competitive package of additional benefits, including health, dental & vision.
• Retirement with company contribution.
• Parental leave & reproductive or family planning support.
• Mental health & wellness benefits.
• Generous PTO and company recharge days.
• Learning & development stipend.
• Work from home stipend and cell phone reimbursement.
• Sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles.