Senior Engineering Manager - Native Ads

Spotify•New York, NY

1d•Hybrid

About The Position

The Music Mission team owns Spotify’s end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale. You’ll join the Native Ads product area within the Music Mission, where we build advertising experiences that feel native to the listening journey while supporting artists and creators at scale. This team sits at the intersection of Music, Advertising, and Personalization, working across missions to deliver impactful, data-driven solutions. We operate in a highly collaborative environment with product, data science, and engineering partners, solving complex machine learning challenges that power ad experiences for millions of listeners around the world.

Requirements

Experience managing managers and scaling engineering organizations through multiple levels of leadership
Strong technical depth and are comfortable engaging in architecture, system design, and complex debugging
Experience with machine learning or probabilistic systems and understand their real-world operational challenges
Make thoughtful, high-quality decisions and bring clarity in complex or ambiguous situations
Build alignment across teams and influence stakeholders at different levels of the organization
Communicate effectively and adapt your approach to different audiences and contexts
Partner closely with product and data leaders to shape strategy, not just execution
Create accountability across teams and address misalignment constructively
Committed to building inclusive teams where diverse perspectives are valued

Responsibilities

Lead and support a team that includes engineering managers and senior engineers, helping leaders grow and scale their impact
Set clear technical and organizational direction across multiple teams, aligning with mission and company priorities
Drive delivery across complex, distributed systems spanning Music, Ads, and Personalization
Stay close to the technology. Contributing to architecture, system design, and critical technical decisions
Partner with product, data science, and design to shape strategy and long-term direction
Navigate ambiguity in machine learning systems, including debugging, experimentation, and incident response
Build strong cross-mission relationships and influence decisions across teams and disciplines
Identify risks early, remove organizational blockers, and ensure accountability at all levels
Foster a culture of ownership, technical excellence, and continuous learning