Analytics Engineer
About The Position
We're looking for an Analytics Engineer to join as an early member of our Data Team and help build the systems that power artist sourcing, track pricing, portfolio management, and catalog growth. This role sits at the intersection of analytics, engineering, and product with high autonomy, technical ownership, and direct business impact. You will report to the Head of Data & Analytics and help define the future of our data products. Because data fuels everything we do, the Data Team works horizontally across the entire company. While your core focus will be deal-flow optimization and catalog pricing - the core of Duetti’s business model - you’ll also collaborate with music-industry veterans, financial experts, and senior engineers and data scientists across a variety of initiatives.
Requirements
- 5+ years in analytics engineering or data analytics roles within high-growth environments
- Strong SQL & Python skills for data modeling, transformation, and automation
- Hands-on experience with BI tools (Looker, Tableau, or equivalent)
- Ability to translate complex data into clear, actionable insights for technical and non-technical stakeholders
- A builder mindset: autonomous, curious, proactive, and excited to shape a fast-moving analytics stack
Nice To Haves
- Experience with music streaming data, KPIs, or creator-economy platforms (preferred but not required)
- Experience collaborating on or implementing LLM-powered internal tools or workflows (preferred but not required)
Responsibilities
- Own the core models, transformations, and analytics products that drive track and catalog pricing decisions
- Partner with Finance & Management to uncover insights into catalog performance, revenue drivers, and portfolio health
- Collaborate with Data Science to refine predictive models and integrate third-party and proprietary datasets
- Work closely with Product to design internal tools, workflows, and decision support systems
- Identify and resolve data quality and pipeline issues, ensuring a reliable analytics foundation across teams
- Dive deep into streaming performance and catalog behavior to uncover optimization opportunities for acquired catalogs
- Explore and build LLM-powered internal tools that automate data workflows
Benefits
- healthcare coverage
- flexible paid time off
- hybrid work model
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
11-50 employees
