Data Analyst

About The Role Our Data Team is looking for a

Data Analyst

to help us build a data foundation that the business can actually trust and use. We’re a music publishing company under 50 people. Our data volume isn’t huge (yet) — but the complexity is very real:

royalty statements, split sheets, ISRC mapping, catalog metadata , and sources that don’t always agree with each other.

So we’re not hiring someone to “manage petabytes.” We’re hiring a

Data Swiss Army Knife : a pragmatic generalist who enjoys turning messy inputs into clean structure, and turning that structure into dashboards that deliver the “Aha!” moment.

Reporting to the

Data Lead , you’ll sit right in the middle of

data engineering x business analytics

— building the backbone first, then turning it into insights that help teams move faster and smarter.

Your Roadmap: Phase 1: Building the Foundation (The First 3–6 Months)

You won't be spending all day in BI tools right away. Your first mandate is to get our house in order. Warehouse Design:

Architect and build pragmatic, scalable data models (e.g., Star Schema). You will create the foundational data warehouse that our entire business will scale on. Data Wrangling:

Ingest and clean messy, fragmented data from various music industry sources (Spotify, Apple, ASCAP, BMI) to establish a reliable single source of truth. Pipeline Management:

Set up the core ETL/ELT pipelines. You know when to build something robust and automated, and when a scrappy solution is enough for now.

Phase 2: Insights, Ad-Hoc & BI (Month 6 and Beyond)

Once the foundation is solid, your focus shifts to the front-end business value. BI & Dashboarding:

Design, build, and maintain intuitive dashboards ([Insert BI Tool]). You’ll turn the tables you built into actionable insights for users who aren't highly technical. Ad-Hoc Analysis:

Dive into the weeds of our catalog and royalty data to answer pressing, complex questions from our A&R, finance, and licensing teams. Data Evangelism:

Train business users on how to self-serve data and trust the metrics you’ve built.

What We’re Looking For: SQL :

You write clean, optimized, and readable queries. Architectural Mindset:

You understand the basics of dimensional modeling (e.g., Star Schema) and how to build a data warehouse from the ground up, even on a small scale. BI Expertise:

Proven experience with visualization tools (e.g., Tableau, Metabase, Looker Studio, PowerBI) and a strong sense of UX for business users. Pragmatism over Perfection:

You know when to build a robust, automated pipeline and when a scrappy, quick ad-hoc pull is what the business actually needs right now. Industry Bonus:

Experience or deep interest in the music industry, specifically publishing, royalties, and catalog management. (If you know what an ISRC or a mechanical right is, you go to the top of the pile).

Requirements Must Have 2–3 years experience in Data Analyst / Analytics Engineer / BI role Strong

SQL

(mandatory) Experience working with

BigQuery or other cloud data warehouses Experience building dashboards for business users Familiar with

dbt or structured data transformation practices Basic to intermediate

Python

for data processing Comfortable working independently in a small team Strong problem-solving and communication skills

Nice to Have Experience in media, music, or digital platform analytics Understanding of dimensional modeling (star schema)