WHO WE ARE:
Splice is a creative platform for people who make music. Serious producers choose Splice Sounds to bring their ideas to life. A subscription to Splice inspires and accelerates creative success for digital music creators with an industry-leading catalog of sounds and samples and an expanding AI stack. With a rent-to-own marketplace of DAWs and plugins, the Splice experience seamlessly integrates into any music production workflow, regardless of DAW (Digital Audio Workstation). Via Splice, an unparalleled team of sound designers and sample creators are fueling the success of a growing global community of chart-topping producers, students, and DIY creators.
HOW WE WORK:
At Splice, DISCO is a rallying cry for collaboration, accountability, and unity within our organization; Direct, Inclusive, Splice Together, Creator Centric, and Optimistic. Our shared success depends on our ability to support one another, work well together, and communicate directly. By embracing flexibility and a unified approach, we can navigate anything that’s thrown at us.
Splice embraces a culture of remote work. You’ll see your colleagues showing up from across the US and the UK. In order to keep us working well as a team, we have regular communication, including Town Halls, departmental all-hands and get-togethers.
When you join Splice, you join a network of colleagues, peers, and collaborators. Are you ready?
JOB TITLE: Data Engineer II
LOCATION: REMOTE- US
THE ROLE:
We're looking for a Data Engineer II to join Splice's Data Engineering team and help scale the platform that powers creator payouts, revenue reporting, and product analytics across Splice's product lines.
Data Engineering builds and maintains the reliable foundation that makes trusted data possible, enabling teams across Splice to work from a governed, consistent source of truth. We are accountable for the warehouse and pipeline foundation; ingestion, transformations, and the standards and quality guardrails that keep data consistent, timely, and usable. This is a mid-level, high-ownership role: engineers here carry features from technical design through delivery, monitoring, and documentation, and participate in our on-call rotation.
The work requires hands-on data engineering experience. Our stack; BigQuery, SQLMesh, Python, Dagster- is distinct from Splice's web engineering stack, and effective contribution requires domain expertise in data pipeline systems, not general software engineering background.
TEAM INFORMATION:
You'll be joining Splice's Data Engineering team, a small, embedded platform team responsible for the pipelines, transformations, and warehouse infrastructure the rest of the company depends on. Our systems support finance-critical processes (contributor payouts, GAAP revenue reporting), product analytics, and data reliability for customer-facing features like recommendations. We operate with a shared on-call rotation and a strong bias toward observable, well-documented, durable systems.
WHAT YOU’LL DO:
Pipeline Development & Transformation
Reliability & Observability
Finance & Revenue Pipelines
Platform Quality & Optimization
JOB REQUIREMENTS:
SPLICE BENEFITS:
The national pay range for this role is $94,952 - $118,690. Individual compensation will be commensurate with the candidate's experience.
Splice is an Equal Opportunity Employer
Splice provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
We’re building a creative ecosystem for music producers. With this ecosystem, we’re cultivating a global community of creators that fosters inspiration, connection, focus, and growth.
Our work environment is no different. We champion collaboration, big ideas, helping where we can and asking for assistance when we need it. We aim for steady, measured expansion through experimentation and iteration. We encourage optimism, inclusion, and transparency in the workplace. We aren’t afraid to stumble, because every stumble can teach us something about our processes, strategies, and even ourselves.