Figma · boards.greenhouse.io · checked today
Data Platform Engineer
<div class="content-intro"><p>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.
Skills, with evidence
- Python
Strong software engineering skills (Python or similar), with experience designing reliable and scalable systems.
must have - Data quality
Improve the reliability of critical data systems through better monitoring, data quality, incident response, upgrades, and performance management.
must have - Airflow / orchestration
Experience improving developer workflows such as local development, testing, CI/CD, orchestration, or deployment.
must have - AWS
Experience with modern data infrastructure, such as cloud data warehouses, transformation frameworks, workflow orchestrators, infrastructure as code, and observability tools.
must have · not practised here - Data modelling
Partner across Data Engineering, Data Infrastructure, Data Science, Research, Modeling Platform, Security, and Product Engineering to define ownership boundaries and supported patterns for batch, micro-batch, reverse ETL, and product-facing delivery.
must have - Governance & security
<li>Make trusted data easier to find and use by establishing clear definitions, ownership, lineage, and reliability expectations</li>
not practised here - Failure handling
<li>Improve the reliability of critical data systems through better monitoring, data quality, incident response, upgrades, and performance management</li>
- Streaming
From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world.
- Machine learning
You’ll work at the intersection of data, infrastructure, and machine learning, building scalable systems that empower Data Science, unlock AI capabilities across the company, and bring data and models closer to the product experience.</p>
not practised here - Terraform
<li>Experience with modern data infrastructure, such as cloud data warehouses, transformation frameworks, workflow orchestrators, infrastructure as code, and observability tools</li>
not practised here
Your plan
- The SQL screen: correct, then fast≈ 1 h
Data quality
- Average order value by countryFoundations
- Bucket missing countriesFoundations
- Customers who never orderedFoundations
- Hiring funnel by roleFoundations
- Orders with no line itemsFoundations
- Python: the data-wrangling round≈ 2 h
Python
- Clean spreadsheet headers into column namesFoundations
- Events normalization jobFoundations
- List the distinct composite keysFoundations
- Deduplicate rows, first one winsFoundations
- Render a byte count for humansFoundations
- Data modelling: the round most people fail≈ 2 h
Data modelling
- Marketplace core entitiesFoundations
- Cinema seat bookingFoundations
- City parking baysFoundations
- Dating app matchesFoundations
- Food delivery ordersFoundations
- Pipeline design: safe to run twice≈ 3 h
Airflow / orchestration · Failure handling · Streaming
- After the first one finishesFoundations
- Run it for last TuesdayFoundations
- The history nobody keptFoundations
- The spreadsheet is a dependencyFoundations
- Too slow by morningFoundations
- Say it out loud≈ 1 h
Not covered by the plan: AWS, Governance & security, Machine learning, Terraform.
Readiness
Counted from drills you have completed anywhere on D8LooP.
leaves in 12 dremoved the moment Figma closes it