Job description

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! 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. If you're passionate about building scalable, high-performance data platforms that empower teams across Figma, we'd love to hear from you! This is a full-time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: 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 We’d love to hear from you if you have: 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 While it’s not required, it’s an added plus if you also have: 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 Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, Claude) to write, debug, and optimize code At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you're excited about this role but your past experience doesn't align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. Figma offers equity to employees, as well as a competitive package of additional benefits, including health, dental, and vision coverage; retirement benefits with company contributions; parental leave and reproductive or family planning support; mental health and wellness benefits; and paid time off. Figma provides paid sick leave, holidays, and other leave benefits in compliance with applicable federal, state, and local laws, including the requirements of the Washington Minimum Wage Act and related regulations. Exempt employees are eligible for employer‑provided paid flexible PTO in addition to flexible paid sick leave. PTO is subject to manager approval. Additional benefits may include company recharge days, cell phone and home internet reimbursements, and a number of lifestyle spending accounts. Figma also offers sales incentive compensation for most sales roles and an annual bonus plan for eligible non-sales roles. All compensation and benefits are subject to applicable plan terms and may be modified by Figma at any time, consistent with applicable law. Annual Base Salary Range: $153,000 — $376,000 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Requirements

Must-haves

This is a full-time role that can be held from one of our US hubs or remotely in the United States.
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
We’d love to hear from you if you have:
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
While it’s not required, it’s an added plus if you also have:
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
Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, Claude) to write, debug, and optimize code
Pay Transparency Disclosure
Examples of accommodations include but are not limited to:

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

figmaaimlmachine learninggolangpythonsqlgo

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Parental Leave

Wellness