We're looking for a customer focused Senior Engineering Manager - Data Platform to support the teams responsible for Depop's data platform. You'll oversee the teams building our foundational data platform - from experimentation, event ingestion pipelines to our data lake, governance frameworks, and data observability and real-time analytics capabilities.

You will work closely with data scientists, machine learning engineers, backend teams, and product leaders to ensure that our data systems are scalable, secure, observable, and enable innovation across the company.

Responsibilities

• Partner with stakeholders across Product, Data, and Engineering to translate strategic goals into platform capabilities.
• Lead and mentor 1-2 squads responsible for experimentation, analytics event logging, batch data platform, real-time infrastructure, data observability and governance.
• Collaborate closely with stakeholders to define and drive the technical roadmap for Depop's modern data platform, enabling reliable and scalable analytics and ML pipelines.
• Advocate for engineering excellence, balancing velocity with long-term maintainability, privacy, and performance.
• Champion data observability and governance, and privacy-by-design principles across the organisation.
• Hire, mentor, and develop high-performing engineers.

• Proven experience managing data infrastructure or platform teams at scale, ideally in a consumer or marketplace environment.
• Deep understanding of distributed systems and modern data ecosystems - including experience with Databrick, Apache Spark, Apache Kafka and DBT.
• Demonstrated success in managing data platforms at scale, including both batch processing and real-time streaming architectures.
• Deep understanding of data warehousing concepts, ETL/ELT processes, and analytics engineering.
• Strong programming skills, particularly in Python, Scala or Java, and a solid understanding of cloud platforms (AWS, GCP, or Azure).
• Experience working with privacy-sensitive datasets and implementing robust data observability and governance.
• A strong technical background - you've built or architected systems hands-on, even if you're now more focused on leadership.
• Track record of building and scaling high-performing engineering teams.
• Ability to think strategically and pragmatically: you can plan for scale and move quickly.
• Excellent communication and collaboration skills; you're comfortable influencing across technical and non-technical stakeholders.

• Experience with machine learning infrastructure or ML Ops practices.
• Familiarity with event-driven architectures in a mobile-first product environment.
• Prior work in fashion, marketplaces, or sustainability-driven tech.