About Suno
We're building the world's first creative entertainment platform, where the entire world can feel the joy and fulfilment of making music. Music is for everyone: Our users include everyone from grandmothers creating songs for their loved ones, to Grammy winners using Suno Studio, our power tool, to make the most popular hits in the world.
Building the future of entertainment requires ambition. The pace is fast, the problems are hard, and the work demands ownership and intensity. For the right people, it’s incredibly rewarding: a chance to shape a new medium, work with a small team that cares deeply about quality, make music, drink too much coffee, and build something that millions of people use to express themselves in ways that were never before possible.
Suno is the fastest growing consumer entertainment company and the leader in AI music. We are backed by leading investors including Menlo Ventures, Lightspeed Venture Partners, Matrix Partners, NVentures (venture arm of NVIDIA).
About the Role
Suno is growing fast, and we’re hiring Staff and Senior Software Engineers to work on Data Infrastructure at Suno, where you will be responsible for building and scaling the foundational systems that power Suno’s data platform. You’ll design and operate the pipelines and infrastructure that ingest, process, and serve PBs of data across the company — enabling everything from analytics and experimentation to machine learning and product features.
This is a high-impact, senior role where you’ll work at the core of Suno’s data ecosystem. You’ll partner closely with Engineering, Data, and ML teams to ensure data is reliable, timely, and scalable, while helping define the long-term architecture of our data platform.
As Suno grows, the complexity and volume of our data will increase significantly. You’ll play a key role in ensuring that our infrastructure can support that growth — building systems that are robust, observable, and easy to extend. Your work will directly influence how quickly and confidently the company can ship, measure, and improve products.
Check out the Suno version of this role here!
What You’ll Do
- Design, build, and maintain scalable data ingestion pipelines using AWS services such as Kinesis, Firehose, Lambda, S3, and Glue.
- Own the architecture and reliability of core data infrastructure, including both streaming and batch pipelines.
- Build and maintain data workflows and orchestration using Dagster, ensuring pipelines are modular, testable, and observable.
- Partner with backend and product engineers to define event schemas, data contracts, and ingestion patterns from production systems.
- Improve the reliability and observability of data pipelines through monitoring, alerting, lineage tracking, and automated recovery mechanisms.
- Collaborate with Analytics and ML teams to ensure the data platform supports a wide range of use cases, from reporting to model training.
- Optimize pipelines and storage for performance, cost efficiency, and scalability across AWS and Snowflake.
- Implement infrastructure as code (e.g., Terraform) to manage AWS and Snowflake resources in a consistent, reproducible way.
- Contribute to data platform standards, including schema evolution, data quality enforcement, and pipeline reliability best practices.
- Lead technical design discussions and help shape the future architecture of Suno’s data platform.
- Mentor other engineers and raise the bar for engineering quality, reliability, and maintainability.
What You’ll Need
- 5-7+ years of experience as a Software Engineer, Data Engineer, or in a similar infrastructure-focused role.
- Strong programming skills (Python preferred) with experience building production-grade distributed systems.
- Deep experience building and operating data pipelines, including both real-time (streaming) and batch processing systems.
- Hands-on experience with AWS data services, including Kinesis (Streams), Firehose, Lambda, and Glue.
- Strong experience with Snowflake, including data modeling, performance optimization, and large-scale data processing.
- Experience with orchestration frameworks such as Dagster (or similar tools like Airflow), with an emphasis on building maintainable, observable workflows.
- Proficiency with dbt for managing transformations, testing, and modular data modeling.
- Experience designing systems for reliability and observability (monitoring, logging, alerting, tracing).
- Familiarity with infrastructure as code (e.g., Terraform) and managing cloud resources programmatically.
- Strong understanding of data warehousing, data modeling, and pipeline design best practices.
- Experience collaborating cross-functionally with data, ML, and product engineering teams.
- Ability to operate in ambiguous environments and make pragmatic, high-quality technical decisions.
- A strong sense of ownership and a track record of delivering scalable infrastructure systems.
- A genuine passion for music, creativity, and AI, and excitement about enabling the next wave of generative creation through robust data infrastructure.
Additional Notes
- Applicants must be eligible to work in the US.
- This is an onsite role in NYC or Boston.
- This is a 5 days a week in-office role.
Perks & Benefits
- Company Equity Package
- 401(k) with 3% Employer Match & Roth 401(k)
- Medical, Dental, & Vision Insurance (PPO w/ HSA & FSA options)
- 11 Paid Holidays + Unlimited PTO & Sick Time
- 16 Weeks of Paid Parental Leave
- Creative Education Stipend
- Generous Commuter Allowance
- In-Office Lunch (5 days per week)
Suno is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.