Senior Engineering Manager – Data Platform

Senior Engineering Manager – Data Platform 1 Day a Week Onsite - London

We are seeking a customer-centric Senior Engineering Manager – Data Platform to lead the teams responsible for building and evolving our core data infrastructure. In this role, you will oversee the development of our foundational data platform — encompassing experimentation frameworks, event ingestion pipelines, data lakes, governance frameworks, data observability, and real-time analytics capabilities. You will collaborate closely with data scientists, machine learning engineers, backend engineers, and product leaders to ensure our data systems are scalable, secure, observable, and foster innovation across the organization.

Key Responsibilities

• Partner with cross-functional stakeholders in Product, Data, and Engineering to align strategic goals with platform capabilities.
• Lead and mentor 1–2 engineering squads focused on experimentation, analytics event logging, batch and real-time data infrastructure, observability, and governance.
• Define and drive the technical roadmap for a modern data platform, enabling reliable, scalable, and efficient analytics and machine learning workflows.
• Promote engineering best practices, emphasizing long-term maintainability, system performance, and privacy by design.
• Champion robust data governance and observability practices across the organization.
• Attract, grow, and retain top engineering talent, fostering a high-performing and inclusive team culture.

Qualifications

• Extensive experience leading data infrastructure or platform teams at scale, ideally in consumer-facing or marketplace environments.
• Strong knowledge of distributed systems and modern data ecosystems, with hands-on experience using technologies such as Databricks, Apache Spark, Apache Kafka, and DBT.
• Proven success in building and managing data platforms supporting both batch and real-time processing architectures.
• Deep understanding of data warehousing, ETL/ELT pipelines, and analytics engineering principles.
• Proficient in programming languages such as Python, Scala, or Java, and experienced with cloud platforms (AWS, GCP, or Azure).
• Experience working with privacy-sensitive data and implementing comprehensive observability and governance solutions.
• Strong technical foundation with a track record of hands-on system design and architecture.
• Demonstrated ability to build and scale high-performing engineering teams.
• Strategic thinker with the ability to balance long-term vision with near-term execution.
• Exceptional communication and collaboration skills, with the ability to influence technical and non-technical stakeholders alike.

Bonus Qualifications

• Experience with machine learning infrastructure and MLOps practices.
• Familiarity with event-driven architectures, particularly in mobile-first environments.
• Background in fashion, marketplaces, or sustainability-focused technology sectors.