Data Enablement Engineer @ Depop
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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.
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.