• Lead multiple engineering teams, owning delivery, technical direction, effectiveness, and overall performance. • Be accountable for performance management outcomes across teams, ensuring consistent feedback, clear expectations, and strong manager and IC development. • Drive technical and operational strategy across squads, optimizing for system level outcomes rather than individual team success. • Partner with product, design, and other stakeholders to define cross team goals, roadmaps, sequencing, and measures of success. • Coach Engineering Managers and ICs, holding them accountable for results and people leadership. • Create clarity in ambiguous environments and stabilize or improve teams facing delivery, technical, or organizational challenges. • Lead complex, cross team initiatives with strong planning around capacity, sequencing, and tradeoffs. • Establish and track metrics to measure progress, using data to inform decisions and continuously improve team effectiveness. • Maintain high standards for technical quality and reliability, ensuring cohesion of technical direction across teams. • Engage in the end-to-end recruiting process, hiring, and on-boarding engineering talent to help grow the team and broader engineering organization.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We're looking for an Engineering Manager to join the Native Ads team in the Music Mission. In Native Ads, we build consumer and industry-facing music promotion products which provide creators new avenues for promoting their work, reaching new audiences, and deepening their connections with fans. You will play an integral role in shaping the future of Native Ads products, technology, and business, and represent Native Ads in the continuously evolving Coordinated Promotions ecosystem by collaborating with key partners in Personalization and Amplify. As the Engineering Manager for the Optimyst Squad, you will solve complex problems surrounding: - Forecasting campaign budgets - Targeting optimization - Observability into campaign delivery systems Your goal will be to improve overall supply and campaign performance and develop solutions to provide engaging music experiences for 350+ million active users using user behaviors and contextual information on mobile and connected platforms. Above all, your work will impact the way the world experiences music and the way creators connect to their fans! Qualifications - Demonstrable success in engineering management, with several years of experience leading and growing engineers - Strong background in statistics/ML/AI technologies and their application to consumer products - Invested in balancing developing thriving engineers and helping teams achieve significant business impact - Thrive in ambiguity, balancing tech health with speed of impact and learning - Strong product intuition to efficiently connect the dots between multiple systems at Spotify - Experience or strong interest in emerging agent technologies and generative recommender systems - Aim to build capabilities that deliver a great, safe, and trusted experience to customers and Spotify users - Understanding of the challenges of deploying and monitoring models in production - Ability to translate product metrics into model improvement strategies - A plus if you have some knowledge of Ads systems Requirements - Lead the team to enhance current Native Ads product performance by experimenting with current and new ML models - Participate in and challenge your team's systems architecture and modeling approaches - Grow the technical expertise of your team through technical leadership and advocating for sound practices - Identify, advocate for, and lead critical initiatives to advance technical and product performance in Native Ads - Manage a team of ML, DE, BE, and Web engineers to develop, maintain, and own business-critical models - Collaborate with a multi-functional, agile team to build new product features - Foster a healthy, collaborative, and productive engineering team - Develop the team’s resilience amid fast change and ambiguity - Grow people and the team through hiring, coaching, mentoring, feedback, and continuous improvement efforts Benefits - Flexibility to work where you work best - In-person meetings with flexibility to work from home - United States base range for this position is $164,448 - $234,926 plus equity - 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

• Own the technical roadmap and make sure every engineering effort maps directly to business impact. • Lead and grow an engineering team that ships fast, iterates constantly, and treats complexity as a cost. • Tackle the hard, multi-layered problem: automated vetting, intelligent matching at scale, demand-side bottlenecks. • Make hard prioritization calls. Decide what we build, what we skip, and what we kill. • Work directly with the founder and product team to define what success looks like before writing a single line of code. • Build the engineering culture: high ownership, high speed, low bureaucracy.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are looking for a Backend Reporting Engineering Manager to lead a team of Data Engineers and Analytics Engineers responsible for the systems that power all reporting analytics at MNTN. This is a hands-on engineering leadership role focused on building and operating production-grade data systems with real SLAs, cost constraints, and failure modes. The ideal candidate has deep experience in Data Engineering, Analytics Engineering or SRE-adjacent roles in production and brings a strong bias toward automation, reliability, and operational excellence. While this role is platform-heavy, it also carries meaningful Product ownership and stakeholder-facing responsibility. The manager is expected to represent the reporting platform with clarity and credibility, translate business needs into durable system design, and ensure that reporting capabilities evolve in lockstep with customer and business requirements. What you'll do - Lead, mentor, and grow a team of Data Engineers and Analytics Engineers responsible for MNTN’s reporting foundation. - Own all analytics business logic and data engineering systems that power reporting, including: - Metric definitions, computation logic, versioning, and change management - ETLs and transformations across the medallion architecture (Bronze, Silver, Gold) - Data quality, reconciliation, validation, and automated testing frameworks - Act as the primary owner of reporting correctness, ensuring consistent definitions and behavior across all downstream consumers. - Establish and enforce data contracts, freshness guarantees, and reporting SLAs in partnership with Product and customer-facing teams. - Drive the design and evolution of reporting schemas optimized for performance, cost efficiency, and ease of extension as requirements change. - Build systems and guardrails that prevent regressions, reduce manual QA, and replace brittle, one-off logic with standard patterns. - Lead incident response for reporting data issues, including stakeholder communication, root cause analysis, and durable remediation. - Partner closely with Program, UI, and API teams to: - Shape reporting requirements early - Clarify tradeoffs between speed, accuracy, and complexity - Support new customer-facing insights without compromising platform stability - Represent the Backend Reporting squad in cross-functional forums, providing clear status, risks, and recommendations to stakeholders. - Continuously improve performance tuning and cost optimization of analytics workloads, particularly in BigQuery. - Set and uphold a high bar for operational rigor, testing discipline, and production readiness across the team. What success looks like - Faster, safer iteration on metrics and KPIs. - Low data incident rates and fast MTTR when issues occur. - Consistent adherence to reporting SLAs. - Measurable reduction in manual QA and rework. - Predictable cost and performance characteristics of analytics workloads. - High trust in reporting data across Product, Engineering, and the business. Qualifications - Proven experience managing Data Engineers, Analytics Engineers or SRE-adjacent Engineers building scalable production data platforms, not just consuming data. - Strong background in data engineering, distributed systems, or platform infrastructure. - Demonstrated ability to balance platform rigor with Product ownership, including shaping requirements and setting expectations with stakeholders. - Deep understanding of SQL-based analytics systems, including schema evolution, backfills, and versioned transformations. - Experience operating data pipelines with defined SLAs for freshness, correctness, and performance. - Hands-on familiarity with modern analytics tooling (e.g., SQLMesh, dbt-class frameworks, Airflow-class orchestration). - Track record of reducing operational toil through automation, standardization, and system-level design. - Experience with data observability, testing frameworks, and incident management in production environments. - Strong stakeholder-facing communication skills, with the ability to explain complex data behavior clearly to non-technical audiences. - Execution-oriented leadership style: you prioritize clarity, accountability, and outcomes over process theater. Benefits - 100% remote within the US - Flexible vacation policy - Annual vacation allowance for travel related expenses - Three-day weekend every month of the year - Competitive compensation - 100% healthcare coverage - 401k plan - Flexible Spending Account (FSA) for dependent, medical, and dental care - Access to coaching, therapy, and professional development