CAREERS

About Us

For over 25 years, Native Instruments has been at the forefront of sonic innovation. Guided by our mission to inspire and enable creators to express themselves, we develop integrated audio hardware and software solutions for musicians, producers, engineers, and DJs of all genres and levels of experience.

Native Instruments embraces diversity and a respect for all people. We are proud to be an equal opportunity employer and we believe the foundation of our dynamic and pioneering spirit starts with a fair and inclusive culture. At Native Instruments we value teamwork and passion, delivering inspiring experiences, continuously innovating and empowering our communities, while also serving our planet.

All applicants will receive equal consideration for employment at Native Instruments and we encourage everyone to apply – regardless of gender identity, race, color, religion, sex, sexual orientation, national origin, genetics, disability, age, or any other characteristic protected by law.

Help us reach our goal in making the future of music diverse, inclusive and exciting! We encourage you to submit your application without the requirement for a photograph, identifying factors or personal status information.

About The Team

You will join the Research team, partnering closely with Product, Design, and Engineering teams across Native Instruments brands. As our Data Engineer, you will build and operate the pipelines and datasets that make high-quality audio and symbolic audio available for experimentation and shipped products, while keeping data secure and compliant. The role is based in our Madrid hub, collaborating daily with colleagues in Boston, Berlin, and London.

Your Contribution

• Build and run reliable pipelines on AWS and Linux compute that turn audio and symbolic audio into model-ready datasets through scalable processing and augmentation, with automated quality checks and data validation.
• Ingest and organize new proprietary data into our systems, structuring S3 prefixes and indexes, and capturing essential metadata for discovery and reuse.
• Publish training and evaluation datasets with clear lineage, versioning, and documentation for reproducibility.
• Improve team efficiency with self-serve tools, orchestration, and monitoring.
• Document pipelines and datasets so others can operate them; reduce single-person dependency and increase resilience.
• Define clear schemas, access controls, and governance practices that keep data secure and compliant.
  
  

Our Ideal Candidate

• Significant years of data engineering experience.
• Strong Python and SQL.
• Hands-on with AWS data services and building batch and streaming data pipelines on S3; comfortable running Python data jobs on containers or Linux compute nodes.
• Experience with data-centric MLOps practices for building and maintaining ML datasets, such as dataset versioning, experiment tracking, data quality validation, and reproducibility, with a basic compliance mindset for licensed audio.
• Good working knowledge of audio datasets or similar streaming real-valued time series; comfortable with sampling rates, channels, time alignment, and audio quality measures (such as S/N ratio, THD, bandwidth), plus common audio formats and representations.
• Clear communicator who collaborates cross-functionally with Research, Product, Design, Engineering, and Research.
  
  

Our Benefits

• Flexible work model from one of our entity locations
• Trust-based working hours
• Holidays: 25 days paid holiday per year
• Global Travel Insurance coverage
• Public Health, Pension & Disability Insurance coverage
• Free software downloads and reduced prices on hardware