Data Enablement Engineer
@ Depop

London, England, United Kingdom
£80,000
On Site
Posted 24 days ago

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Job Details

About Depop

Depop is the community-powered circular fashion marketplace where users buy, sell and discover secondhand fashion. With over 35 million users and backed by Etsy, Depop champions diversity and sustainability in fashion.

Role Overview

The Data Enablement Engineer at Depop will architect, build, and scale our data platform, enabling self-serve capabilities for teams across the organization. You will collaborate with Insights, Analytics Engineers, Data Scientists, MLOps, MarTech, and other Data Engineering teams to support complex business problems and drive data-as-a-product practices.

Responsibilities

  • Pave a path for data as a product by introducing robust data observability and governance.
  • Develop microservices, libraries, and data pipelines under software engineering best practices.
  • Design and implement platform services using modern tools like Kafka, Terraform, Docker, etc.
  • Lead initiatives with data scientists, ML engineers, and analytics teams to support data needs.
  • Maintain operational excellence through scalable services, incident response, and documentation.

Technology & Tools

Work with state-of-the-art data stack components including Airflow, Databricks, Kafka/Confluent, dbt, and streaming technologies. Emphasis is on scalable infrastructure, automation, and data governance solutions.

Key Skills/Competency

  • Data Platform
  • Data Pipelines
  • Streaming
  • Microservices
  • Governance
  • Automation
  • Python/Scala
  • Cloud Infrastructure
  • Collaboration
  • Scalability

Perks & Benefits

Enjoy health and wellbeing benefits, flexible hybrid working, generous leave policies, professional development opportunities, and unique Depop extras including free shipping on sales and company milestones rewards.

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How to Get Hired at Depop

🎯 Tips for Getting Hired

  • Research Depop's culture: Study their mission, values, and recent news.
  • Customize your resume: Highlight data platform and streaming skills.
  • Showcase technical expertise: Emphasize Python, Kafka, and cloud experience.
  • Prepare for interviews: Review data engineering design and governance cases.

📝 Interview Preparation Advice

Technical Preparation

Review Kafka and streaming system concepts.
Practice coding in Python and Scala.
Study cloud-native and containerization patterns.
Refresh data pipeline and orchestration tooling basics.

Behavioral Questions

Describe past cross-team collaboration experiences.
Explain how you manage project deadlines.
Share a mistake and how you resolved it.
Discuss handling complex stakeholder requirements.

Frequently Asked Questions