Spotify

• Build and evolve Groove, a fullstack platform that supports planning, collaboration, and execution across Spotify. • Design and deliver features including initiative tracking, planning workflows, and dependency management. • Work across the stack using React, TypeScript, Java, GraphQL, PostgreSQL, and Google Kubernetes Engine (GKE). • Partner closely with product managers and designers to understand user needs. • Ensure reliability through testing, monitoring, and continuous improvement in production. • Participate in an on-call rotation and help respond to production incidents. • Improve performance, scalability, and maintainability of frontend and backend systems. • Use AI-assisted development tools to improve productivity. • Lead the design and delivery of complex features across the stack. • Own problems end-to-end, from requirements through to solutions. • Help define and evolve architecture across frontend, backend, and infrastructure. • Mentor engineers and contribute to raising the technical bar.

• Own and improve the machine learning models and systems that power the Home feed. • Design, build, and ship personalized recommendations serving millions of Spotify listeners globally. • Build content recommendation systems for emerging AI-powered user experiences. • Train, fine-tune, evaluate, and optimize large language models using various techniques. • Partner with product managers, engineers, data scientists, and designers to execute experimentation strategies. • Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency. • Improve ML platform capabilities, data pipelines, and production systems that support personalization. • Drive technical direction in ambiguous problem spaces and contribute to long-term architecture of personalization systems. • Mentor and support other machine learning engineers, helping raise the bar across the team.

• Lead, coach, and develop a team of machine learning engineers, creating an inclusive, high-performing engineering culture. • Set the technical direction for the team while partnering with Product, Data Science, and Engineering leaders to deliver impactful machine learning capabilities. • Guide the design, development, deployment, and operation of production machine learning systems at scale. • Support engineers through technical mentorship, career development, performance management, and regular feedback. • Drive execution by helping the team prioritize work, remove obstacles, and continuously improve delivery. • Foster engineering excellence through modern software engineering practices, experimentation, and operational excellence. • Partner across squads and missions to influence technical strategy and ensure alignment across the Personalization organization. • Champion thoughtful adoption of emerging machine learning technologies, including large language models, where they create meaningful user value.

• Build end-to-end features across modern web applications, backend services, and data platforms that support Spotify's global subscription business. • Create intuitive internal products that enable business teams to launch, configure, and manage Premium offers through secure, guided workflows. • Design, develop, and maintain scalable backend services that power subscriptions, prepaid products, pricing, promotions, and the offer lifecycle. • Develop GraphQL and gRPC APIs that connect frontend applications with distributed platform services. • Design efficient database schemas, implement data migrations, and optimize application performance using PostgreSQL. • Build secure, reliable, and auditable systems that support business-critical financial operations and SOX-compliant approval workflows. • Collaborate with engineers across the Subscriptions Mission to evolve shared platform capabilities, improve developer experience, and increase platform reliability. • Write maintainable, well-tested code while contributing to technical design, architecture discussions, code reviews, and continuous improvement. • Participate in an on-call rotation to help maintain the reliability and availability of services powering Spotify Premium.

• Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain, identifying opportunities that improve scalability, reliability, and business impact. • Design scalable batch and streaming data platforms that power analytics, experimentation, machine learning, and subscriber experiences. • Partner with Product, Engineering, Data Science, Analytics, and Platform teams to turn complex business challenges into durable, well-designed data solutions. • Lead architectural decisions and establish engineering best practices for data quality, governance, observability, reliability, and operational excellence across multiple squads. • Design data models and platform architecture that support sustainable growth toward one billion users while balancing performance, cost, and maintainability. • Simplify complex systems, reduce technical debt, and improve the developer experience across the broader data ecosystem. • Mentor senior engineers, influence technical direction through collaboration, and help foster a culture of thoughtful engineering, knowledge sharing, and continuous improvement.

• Own and improve the machine learning models and systems that power the Home feed, including the Shortcuts experience. • Design, build, and ship personalized recommendations that serve millions of Spotify listeners globally. • Build content recommendation systems for emerging agentic and AI-powered user experiences. • Train, fine-tune, evaluate, and optimize large language models using techniques such as supervised fine-tuning (SFT), distillation, and parameter-efficient training approaches. • Partner closely with product managers, engineers, data scientists, and designers to define and execute experimentation strategies. • Drive A/B testing, monitoring, model evaluation, and continuous optimization of recommendation quality, reliability, and cost efficiency. • Improve ML platform capabilities, data pipelines, and production systems that support personalization at Spotify scale.

• Lead and develop a team of six experienced engineers • Accountability for team delivery • Partner with product and stakeholders for roadmap shaping • Drive technical strategy and architectural decisions • Build a culture of ownership, psychological safety, and continuous improvement • Collaborate across Data Platform and wider engineering organisation • Manage on-call health, operational excellence, and reliability • Participate in hiring and onboarding

• Define the long-term vision, strategy, roadmap, and execution for Habit Formation across Spotify's consumer experience. • Build the behavioral intelligence that helps identify when listeners are ready to discover new formats, features, or experiences. • Partner with engineering, machine learning, design, research, and data science to build experiences powered by behavioral insights and experimentation. • Translate advances in AI, recommendation models, and intelligent agents into intuitive consumer experiences that millions of listeners love. • Develop systems that encourage sustainable engagement while ensuring teams work together instead of competing for user attention. • Influence the evolution of Spotify's surfaces, information architecture, and product experiences to reinforce lasting listening habits. • Use experimentation, behavioral analysis, and user research to identify opportunities and make informed product decisions in ambiguous problem spaces. • Set clear product direction, make thoughtful prioritization decisions, and align senior leaders around a shared strategy. • Drive execution across multiple engineering teams while balancing quality, speed, user trust, and long-term business impact. • Establish Habit Formation as a strategic product capability that enables sustainable growth across Spotify.

• Define the product strategy and roadmap for a portfolio of User Platform products spanning account lifecycle management, IAM analytics, and device and client intelligence. • Partner closely with engineering managers, staff engineers, data scientists, analytics engineers, designers, researchers and insights teams to shape product direction and deliver long-term platform value. • Collaborate across missions, studios and product areas to ensure Spotify's identity and user data platform evolves to meet business and customer needs. • Help build Spotify's account lifecycle platform with well-defined account states, governed lifecycle transitions and comprehensive audit capabilities supporting Engineering, Customer Service, Legal and partner teams. • Lead the product vision for User Intelligence, the shared platform that enables trusted understanding of users, devices and sessions through reusable signals and APIs. • Partner with teams across User Fraud, Subscriptions, Advertising, Personalization, Safety, Legal and Platform to ensure trusted identity data becomes a strategic input for decision making. • Translate complex identity, trust and data challenges into clear product strategies, business outcomes and prioritization decisions. • Define success metrics including platform adoption, signal quality, data trust, lifecycle diagnosis time, decision latency and reduction of fragmented local solutions. • Balance long-term platform investments with near-term business priorities, regulatory requirements and user experience. • Foster an effective product operating rhythm across multiple squads by creating clarity, alignment and shared ownership that enables teams to move with confidence.

• Build, operate, and evolve scalable Scio data pipelines on Google Cloud Platform that process high-volume financial data with accuracy and reliability. • Develop and enhance Java backend services that power integrations across Spotify's financial ecosystem. • Design and evolve data models and datasets that support accounting, reconciliation, financial reporting, and operational insights. • Build and improve integrations with external financial systems to bring critical financial data into Spotify's financial ecosystem. • Partner closely with Finance, Product, and Engineering teams to translate accounting requirements into reliable, scalable technical solutions. • Improve the scalability, observability, and resilience of financial data pipelines and backend services. • Contribute to engineering best practices through continuous delivery, automated testing, monitoring, and thoughtful code reviews. • Help drive technical decisions that improve the long-term maintainability of Spotify's financial engineering platform.