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Описание вакансии
Текст:
TL;DR
Data Platform Engineer (AI): Building foundational data platforms and self-service tools for analytics, Data Science, and production-grade AI systems with an accent on scalable infrastructure, developer workflows, and reliable data delivery. Focus on designing batch and micro-batch pipelines, improving CI/CD and observability, and defining ownership and lineage across shared data systems.
Location: Remote within the United States or from Figma hubs in San Francisco, CA and New York, NY; in-person onboarding required
Annual base salary: $153,000–$376,000 USD
Company
Figma develops a collaborative design platform that helps teams create, prototype, translate designs into code, and work together in real time.
What you will do
- Build and evolve shared data platform systems supporting analytics, Data Science, and data-driven product development.
- Improve local development, testing, CI/CD, staging, and deployment workflows for data systems.
- Create self-service tools and reliable paths for building, deploying, and operating data pipelines.
- Improve monitoring, data quality, incident response, upgrades, and performance management for critical systems.
- Establish data definitions, ownership, lineage, and reliability expectations.
- Partner with Data Engineering, Data Infrastructure, Data Science, Research, Modeling Platform, Security, and Product Engineering on batch, micro-batch, reverse ETL, and product-facing delivery patterns.
Requirements
- 5+ years of experience building and operating production data platforms, developer infrastructure, or distributed systems.
- Strong software engineering skills with Python or a similar language, including reliable and scalable system design.
- Experience improving local development, testing, CI/CD, orchestration, or deployment workflows.
- Experience with cloud data warehouses, transformation frameworks, workflow orchestrators, infrastructure as code, and observability tools.
- Experience owning shared systems end to end, leading ambiguous cross-functional projects, and communicating with Data Science, Infrastructure, and Product Engineering partners.
Nice to have
- Experience supporting machine learning or research data workflows.
Culture & Benefits
- Equity and competitive employee benefits.
- Health, dental, and vision coverage.
- Retirement benefits with company contributions.
- Parental leave, reproductive and family planning support, and mental health and wellness benefits.
- Paid time off, paid sick leave, holidays, flexible PTO for eligible exempt employees, and possible recharge days.
- Additional benefits may include cell phone and home internet reimbursements and lifestyle spending accounts.
Hiring process
- Qualifications, job level, and compensation are assessed during the interview process.
- Video interviews require candidates to keep their cameras on.
- In-person onboarding is required after hiring.
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