# Engineering Manager - Data Platform

**Company:** [Spotify](https://hotfix.jobs/companies/spotify)
**Location:** Remote
**Role:** Engineering Management
**Experience:** 5+ years
**Skills:** Distributed Systems, Event-Driven Architecture, Data Infrastructure, Data Platforms, Privacy Infrastructure, AI, LLMs, Technical Strategy
**Posted:** 2026-07-21

> Leads a team of experienced engineers responsible for large-scale event delivery and privacy infrastructure. The role combines people leadership, technical strategy, delivery accountability, reliability, and career development across a distributed European team.

## Job Description

## Responsibilities
- Lead and develop a team of six experienced engineers, focusing on coaching, career development, and creating an environment where people can do their best work.
- Own team delivery through clear priorities, healthy execution, and measurable outcomes.
- Partner with product and stakeholders to shape the roadmap for event delivery and privacy infrastructure.
- Drive technical strategy and architectural decisions for large-scale systems.
- Build a culture of ownership, psychological safety, and continuous improvement.
- Collaborate across Data Platform and the wider engineering organization on shared goals and dependencies.
- Manage on-call health, operational excellence, and service reliability.
- Participate in hiring, onboarding, and capability development.

## Requirements
- Experience managing teams of senior or experienced engineers.
- Strong people leadership skills, including meaningful development conversations and career progression support.
- Experience with distributed data systems, event-driven architectures, or large-scale data infrastructure.
- Ability to engage credibly in technical discussions and unblock engineering teams.
- Track record of accountability for outcomes.
- Clear communication and ability to build trust across functions and time zones.
- Experience working with distributed teams and creating cohesion and inclusion remotely.
- Interest in using AI and LLMs to improve engineering workflows and data infrastructure operations.

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