Sr. Director, Data Analytics & Analytics Engineering

About the Role

Key Responsibilities

• Lead a team of high performing Data Analysts and Analytics Engineers to develop scalable self-service reporting solutions and address diverse ad-hoc requests that transform the business.
• Utilize data visualization to support decision-making by crafting compelling dashboards for key business stakeholders.
• Work with domain experts to develop and deploy business logic onto large and complex raw datasets.
• Collaborate with the global Analytics team and international colleagues to promote a data-driven culture by proposing innovative initiatives and building actionable data products.
• Interact with developers, data engineers, and management to propose new technologies, processes, and system improvements, and develop global data governance strategies.
• Embed value-adding technologies, including Gen/Agentic AI, into workflows to enhance operational efficiency.

Requirements

• Extensive experience in a related role with proven leadership experience.
• Experience in building and managing a high performing team of data analysts.
• Profound experience of SQL-based data analysis on large datasets.
• Advanced knowledge of Python and common data analytics packages such as pandas, NumPy, Matplotlib, and/or Streamlit.
• Experience managing self-service BI tools for large and diverse customer pools.
• Proven ability to quickly explore and grasp new technologies, data models, and business processes.
• Strong written and verbal communication skills for technical and non-technical audiences.
• Impeccable project management skills to deliver high-quality, complex initiatives on time.

Nice to Have

• Experience using components in the existing data analytics and product management stack (GCP, dbt, Looker, Git, Airflow, Docker, Jira, Confluence).
• Experience with music industry data, particularly Music Publishing (Copyright, Royalties) and recorded rights administration data (Royalty, Sales/Usage).
• Understanding of advanced data analysis methodologies such as machine learning, data science, or statistics, and knowledge of data modeling and data product design.
• Strong advocate for training, implementation, and support of self-service data tools within the business.

Qualifications

• Bachelor's or Master's degree in a related field (preferred).

Benefits & Perks

• Hybrid work setup: 3 days in office, 2 days remote.
• Comprehensive medical, dental, and vision coverage.
• Dollar-for-dollar 401(k) match of up to 6% after the first year.
• Flexible time off policy allowing time off when needed.
• Commuter benefits program.
• Fitness reimbursement and wellness incentives.
• 24/7 well-being support through Employee Assistance Program.
• Summer Fridays to kick off weekends early.
• Development opportunities including mentorship and LinkedIn Learning.
• Access to artist showcases and playbacks.