Data Engineer - Royalties

We're working with a growing music & royalties business that provides services across royalty data, rights management, audit, and transactional services. This is an exciting opportunity to join a specialist team in a collaborative, agile environment and gain hands-on experience in the music space!

Responsibilities:

• Build, maintain, and optimise data pipelines for ingestion, transformation, and analysis of royalty datasets

• Clean, standardise, and structure raw, inconsistent datasets to support valuation and due diligence work

• Develop, test, and document transformation processes, applying data quality checks and validation

• Collaborate with the Transaction Services and central data teams to deliver accurate, actionable insights

• Contribute to internal projects, including development of dashboards, front-end applications, and analytical tools

• Apply best practices in version control, CI/CD, and cloud infrastructure management

• Identify opportunities to improve processes, systems, and data quality across the business

Requirements:

• Strong experience in SQL, Python, Spark, and cloud infrastructure (AWS, Databricks preferred)

• Hands-on experience building production data pipelines, coding transformations (e.g., dbt), and implementing data quality controls

• Familiarity with version control (Git), CI/CD concepts, and BI tools (e.g., Tableau)

• Experience handling large, inconsistent, or non-standard datasets with attention to accuracy and detail

• Understanding of medallion architecture and related data concepts

• Knowledge of ML or LLM applications, front-end development (Streamlit, Dash, React), or financial reporting is a plus

• Typically 3-5 years' experience in a Data Engineer or equivalent role

• Analytical, proactive, and solutions-oriented, with the ability to work independently and manage multiple priorities

• Collaborative, adaptable, and comfortable in a fast-paced, high-growth environment

• Interest in music rights, intellectual property, or financial data analysis is advantageous but not essential

Handle actively welcomes applicants from under-represented backgrounds - we pride ourselves on attracting the best talent for every opportunity through a commitment to equality, diversity and inclusion.