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Depop

Peer-to-peer fashion marketplace with commissions

Senior Data Platform Engineer - Data Infrastructure

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Advanced knowledge of a high-level programming language such as Python or Scala, with software engineering best practices including testing, clean coding standards, code reviews, pair programming, and an automation-first mindset.
  • Hands-on experience designing, building, and scaling complex data systems and backend infrastructure in production cloud environments such as AWS, GCP, or Azure.
  • Ability to define long-term technical strategies and execute rapidly.
  • Ability to influence technical direction and align diverse technical and non-technical stakeholders, including ML engineers, analysts, analytics engineers, Product, Marketing, and leadership; understand their needs and how they operate.
  • Expertise managing and integrating data orchestration and processing tools and platforms such as Databricks, Airflow, dbt, and Kafka or similar.
  • Experience with agentic coding tools such as Claude Code or Cursor.

Responsibilities

  • Champion data as a first-class citizen by introducing robust data capabilities, observability, and governance into the platform to enable decision-making and improve end-user experience.
  • Develop microservices, libraries, platforms, and tools.
  • Architect and evolve platform services that enable teams to work with data efficiently and securely at scale.
  • Lead large, complex initiatives that enable data users by setting vision and roadmap, gathering requirements, and defining scope and success metrics while applying a platform-as-a-product approach.
  • Automate infrastructure and monitoring, lead incident response and root cause analysis, and continuously improve the health and performance of the data platform.
  • Promote scalable standard processes through automation, clear documentation, and knowledge sharing via tutorials and training sessions.
  • Establish trusted relationships with technical and non-technical stakeholders to define, design, and implement data platform solutions.
  • Contribute to group and peer-level initiatives to improve the data platform.
  • Mentor others and share knowledge to elevate technical standards and foster continuous improvement.
  • Actively improve Depop's engineering culture and encourage others to follow its values.

Desired Qualifications

  • DevOps experience building CI/CD pipelines with Jenkins or GitHub Actions, and infrastructure as code with Terraform.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Hands-on expertise with Spark.
  • Advanced experience working with and understanding the tradeoffs of at least one data lake table or file format: Delta Lake, Parquet, Iceberg, or Hudi.
  • Experience with lakehouse or medallion architectures in Databricks.
  • Experience with Kafka, Flink, Confluent, or other streaming ecosystems, with a solid understanding of their components.
  • Experience with data governance, observability, and catalog solutions such as Monte Carlo, Atlan, or DataHub, enabling data lineage, data contracts, SLA/SLO, tagging, and data quality monitoring.
  • Curiosity about AI and willingness to explore how it can enhance day-to-day work.

About the Company

Depop

Peer-to-peer fashion marketplace with commissions

Depop is a peer-to-peer online marketplace for fashion where users buy, sell, and discover unique items such as vintage pieces, streetwear, sneakers, and designer pieces. Items are listed by users who set prices and descriptions; buyers purchase through the platform, and Depop earns revenue by taking a commission on each sale. The product works through user-generated listings, a social-feel interface with following and messaging, and a payments process that handles transactions. Depop differentiates itself from competitors by targeting a young, fashion-forward audience with a strong emphasis on sustainability, second-hand items, and community engagement, along with a marketplace that blends social discovery with shopping for both well-known brands and independent designers. Its goal is to grow a global, diverse fashion ecosystem where people can easily buy and sell unique, sustainable clothing items while connecting with others who share interest in fashion.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$100.1M
Headquarters
London, United Kingdom
Founded
2011

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