About the role
We are looking for an Engineering Manager to drive Advertising engineering leadership and practices. In this role, you will be instrumental in growing the team and guiding development to successfully scale. You will help us to create a user-first ad experience that's personalized and relevant so we can grow to billions of fans, increasing engagement with our listeners and providing better value to our advertisers. Above all, your work will impact the way the world experiences music. This squad is responsible for the foundational data, services, and tooling that power the ad-serving ecosystem, with a focus on three core areas: Data Architecture and Integrity, Targeting Data Propagation, and Observability and Debugging. They design and own the data architecture to ensure the accuracy and timeliness of core ad-serving datasets for pacing, billing, and business analysis. They also manage the services and pipelines that reliably deliver critical user-targeting information—such as privacy preferences, ad history, and audience segment data—to the ad-serving path. Furthermore, the team develops tools and mechanisms to enhance telemetry within the ad-serving stack, enabling more effective debugging and easier evaluation of system changes, while also providing necessary support for new feature development by handling their specific data and event functionality requirements. \n What You'll Do Build and lead a robust team of data and backend engineers by attracting top talent, mentoring individuals and managing conflict. Work with product managers and lead the team to design and implement product features, while improving the quality of the current big-data intensive tools that exist for audiences and targeting. Lead the team to utilize, homogenize and make available for peer teams to use, diverse large-volume datasets built around user preferences, behavior, identity and location - gathered from a user's mobile as well as other connected platforms. Strong understanding of how data-intensive systems are expressed in the UX shown to customers. Grow the technical expertise of the team around system design, quality and testing, scalability, performance and fault tolerance. Manage OKRs, roadmaps, career conversations, performance and accountability, and thereby carefully plan, track, and report on work of the team and identify problems early. Work closely with many peer teams to ensure that our systems are designed in a scalable and maintainable manner. Nurture a culture of technical quality from design, through code review, to production. Drive optimization, testing and tooling to improve data quality. Who You Are You have experience in leading, managing, coaching and mentoring software developers You have 6+ years Experience in object-oriented programming including Java, Python. You have experience working with high volume heterogeneous data, with data tools such as Hadoop, You have experience with BigTable, BigQuery and Hive. You have experience in data modeling, data access and data storage techniques. You have designed and built distributed production services / pipelines with data processing frameworks like Scio, Storm, Spark and the Google Cloud Platform. You have led agile ceremonies including sprint planning, daily standups and retrospectives You have experience with yearly and quarterly project roadmap planning including sizing, scoping, prioritizing, sequencing and defining external dependencies You have mentored and coached software engineers Where You'll Be We offer you the flexibility to work where you work best! For this role, it can be within the North America region in which we have a work location This team operates within the Eastern Standard time zone for collaboration \n The United States base range for this position is $164,448.00 - $234,926.00, plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.
