Digital Music Jobs (NOW HIRING)

• Champion AI-ready data products by ensuring trusted business definitions, semantic consistency, metadata, lineage, observability, documentation, and governance are embedded into every streaming and social data product.
• Ensure data products are designed to support emerging AI capabilities—including semantic retrieval, recommendation systems, intelligent agents, and LLM-powered experiences—through high-quality, well-governed enterprise data.
• Partner with Commercial Strategy, Global Insights, Label Analytics, Marketing, Finance, and Digital Business teams to define trusted business metrics, KPIs, and standardized consumption definitions.
• Manage the lifecycle of external consumption data sources, ensuring licensed datasets are consistently ingested, governed, documented, monitored, and integrated into trusted enterprise data products.
• Define scalable dimensional models and semantic layers supporting streaming activity, audience engagement, artists, releases, tracks, playlists, social engagement, territories, and commercial performance.
• Establish authoritative data products that serve as the source of truth for music consumption performance across labels, artists, releases, and markets.
• Standardize business definitions for metrics, including streams, listeners, followers, saves, playlist reach, engagement, audience growth, chart performance, market share, and consumption trends.
• Partner with engineering teams to implement SLAs, monitoring, observability, incident management, and operational support processes.
• Establish and maintain data contracts with internal and external consumption data providers to improve reliability and predictability.
• Drive adoption of consumption data products through business-friendly documentation, semantic models, stakeholder enablement, and training.
• Evaluate opportunities to improve business outcomes by applying AI to music consumption, audience behavior, and content performance while maintaining strong governance and data quality standards.

• 5+ years of product management experience supporting digital music, streaming, audience analytics, media, entertainment, or digital content organizations.
• Experience delivering data products that support AI, machine learning, predictive analytics, or generative AI initiatives.
• Strong understanding of the digital music ecosystem, including streaming platforms, social media platforms, audience measurement, and music consumption trends.
• Experience working with music consumption datasets, including streaming activity, artist performance, release performance, audience engagement, playlists, social signals, and chart data.
• Familiarity with industry data providers and platforms such as Spotify, Apple Music, YouTube, Amazon Music, TikTok, Meta, Luminate, Chartmetric, SoundCloud, Pandora, or similar consumption and audience analytics platforms.
• Understanding of artist lifecycle analytics, audience development, catalog performance, playlisting, fan engagement, and commercial music performance measurement.
• Demonstrated experience owning data products throughout their lifecycle, from strategy and requirements through adoption and operational support.
• Demonstrated ability to leverage modern AI tools to accelerate product discovery, documentation, analysis, and collaboration.
• Strong understanding of the data foundations required for enterprise AI, including dimensional modeling, data warehousing concepts, data marts, semantic layers, and modern analytics architectures.
• Experience in defining and managing data quality frameworks, governance standards, and operational reliability practices.
• Experience in establishing and managing data contracts and cross-functional data ownership models.
• Strong SQL proficiency preferred, with the ability to independently validate requirements and investigate data issues.
• Proven ability to translate complex technical concepts into clear business outcomes and stakeholder value.
• Exceptional stakeholder management, communication, and influence skills.
• Strong systems thinker with a customer‑centric product mindset.

Demonstrates expertise in managing AI-ready data products, ensuring high-quality data governance, and driving stakeholder engagement through effective communication and documentation. Proficient in leveraging data analytics and modern AI tools to enhance music consumption insights and audience behavior analysis.

• Product Management Experience
• Data Governance Standards
• SQL Proficiency
• AI and Machine Learning Initiatives
• Digital Music Ecosystem Knowledge

• Data Product Lifecycle Management
• Dimensional Modeling
• Data Warehousing Concepts
• Semantic Layer Development
• Predictive Analytics
• Audience Measurement
• Data Quality Frameworks
• Operational Reliability Practices
• Stakeholder Enablement
• Business Metrics Definition

• Exceptional Communication Skills
• Stakeholder Management
• Customer-Centric Mindset
• Influence Skills
• Systems Thinking

• Digital Music
• Streaming Platforms
• Audience Analytics
• Music Consumption Trends
• Commercial Music Performance

• Spotify
• Apple Music
• YouTube
• Amazon Music
• TikTok
• Meta
• Luminate
• Chartmetric
• SoundCloud
• Pandora