Manager, Software Engineering - Data Platform

Figma is hiring a Manager, Software Engineering - Data Platform to lead and scale the engineering team responsible for its data platform. The role sets technical direction and roadmap, drives platform reliability and delivery, and partners across the company to support data-driven work.

Responsibilities:

• Lead and grow a team of engineers building and operating Figma's data platform, owning delivery, technical direction, and team health
• Set the roadmap and technical strategy for your sub area, and provide hands on technical leadership where the team needs it
• Drive the reliability, scalability, and forward strategy of the platform as adoption grows across the engineering and product organization
• Hire, grow, and coach engineers and tech leads, raising the bar and building a healthy, inclusive, high-performing team
• Partner with Data Science, Product, Finance, and Engineering to identify the highest-leverage priorities and drive alignment
• Make sound build versus buy decisions, including evaluating and managing platform vendors where it makes sense
• Keep delivery predictable while balancing near-term execution with long-term platform investment

Requirements:

• 3+ years managing engineers, including senior ICs or tech leads, with a track record of building and scaling high-performing teams
• Demonstrated experience building and scaling data platform or data infrastructure systems in a production, online environment
• A strong software engineering background with senior or staff-level technical depth before moving into management, and enough current depth to set direct technical direction
• Strong partnership mentality and the ability to manage multiple cross-functional stakeholder groups such as Data Science, Product, Finance, and Engineering
• Ability to set technical direction, drive alignment, and prioritize clearly under ambiguity, paired with strong written communication
• Expertise in large-scale data processing systems, including batch, streaming, or applied AI and ML workloads
• Familiarity with experimentation or feature flagging platforms
• A track record of evaluating and managing vendor relationships
• A demonstrated ability to develop tech leads and scale hiring at pace