Depop runs a London-based resale marketplace on a JVM-heavy stack (Scala, Java, Kotlin) with Kafka, Databricks, dbt and Airflow underpinning a streaming data platform. Hiring is accelerating and skews toward senior and staff engineering and data roles, with job posts focused on Kafka Connect ingestion, data contracts and ML ranking, plus a recurring push to help new sellers land their first sale.
Depop operates a peer-to-peer marketplace where consumers buy, sell and discover secondhand clothing, from everyday pieces to vintage and designer items. Founded in 2011 and headquartered in London, the company also has an office in New York and employs 501–1,000 people. Its native mobile apps are built with Swift and Kotlin, and payments run through Stripe. Infrastructure sits on AWS with Kubernetes, Terraform and Datadog, while customer support uses Zendesk. Current hiring spans the United Kingdom and United States.
Depop uses Scala, Java, Kotlin, Swift and Python, with Kafka, PostgreSQL, DynamoDB, Databricks, dbt and Airflow for data, all running on AWS with Kubernetes, Terraform and Datadog.
Yes. Hiring is accelerating and centers on engineering and data, with mostly senior and staff roles in the UK and US working on streaming pipelines, data contracts and real-time analytics.
Job posts point to simpler seller onboarding, seller milestones, a ranking platform, product matching models, a Kafka Connect streaming pipeline and a data lake for real-time analytics.
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Depop's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
