Senior Data Engineer, Genius

Genius is the leading destination for music, lyrics, and the stories behind the songs—and part of the Media Lab portfolio of digital brands. Media Lab is a media and technology company that acquires and grows category‑defining properties, providing the scale, resources, and expertise to help them thrive. As one of Media Lab’s flagship brands, Genius benefits from this shared foundation while maintaining its unique identity at the intersection of music and culture.

Your Role at Genius
Genius is looking for a remote Senior Data Engineer to help build the ultimate music companion. Overseeing millions of pages of lyrics, annotations, and music metadata, your work will power , our public API, and our partner integrations, with no shortage of interesting data challenges to solve. We're looking for engineers who thrive in complex backend systems: folks who can build robust data pipelines, optimize query performance at scale, and keep critical services running smoothly.

As a Senior Data Engineer for Genius, you will play a key role in strengthening our data infrastructure, helping us process, transform, and serve the music knowledge that powers everything we do. You will work across our Rails backend, Postgre

SQL databases, and Python‑based data pipelines to improve data reliability, throughput, and accuracy. Additionally, you'll work to improve the stability, performance, and scalability of Genius' backend services, which is no small feat for a platform serving millions of users daily!

Location Requirement: Candidates must be based in Los Angeles, California, or Seattle, Washington to be considered for this role.

• Build and maintain data pipelines using Python and Airflow to ingest, transform, and enrich music metadata from internal and external sources
• Proactively identify and fix infrastructure bottlenecks to scale backend services to tens of thousands of requests per minute
• Architect database query patterns and migrations in Postgre
  
  SQL, Clickhouse, and Big Query that scale to large tables with 1B+ rows
• Design and implement backend APIs in Ruby on Rails that serve data reliably and performantly to our frontend and partner integrations
• Take ownership over the systems you build, proactively identifying and surfacing performance, reliability, and maintainability improvements
• During your on‑call rotation, be the backstop for backend quality, stability, and performance. Triage incoming issues to find the most urgent problems, and handle emergent incidents to keep services online
• Work directly with stakeholders to uncover and address business needs, including product owners, data analysts, and other engineers across the company

• Data Pipeline
  
  Experience:
  
  Hands‑on experience building and maintaining ETL/ELT pipelines using Python and workflow orchestration tools like Apache Airflow. Comfortable with data modeling, scheduling, monitoring, and debugging complex pipeline DAGs.
• Database Expertise: Deep proficiency with Postgre
  
  SQL and relational databases. Able to design database schemas, write complex queries, optimize performance for scale, and manage migrations on large, high‑traffic tables.
• Backend Framework Proficiency: Strong experience with Ruby on Rails (or a similar “batteries‑included” framework). Comfortable working with large, established codebases, and understanding of architectural patterns necessary to build APIs at scale.
• Product Ownership: Brings a product‑first mindset, able to drive projects from ideation to launch while focusing on data quality, system reliability, and cross‑functional alignment.
• Collaboration & Communication: Comfortable working cross‑functionally with frontend engineers, data analysts, product, and other teams to ensure clarity, alignment, and smooth execution of projects.
• Continuous Learning: Demonstrates a passion for staying current with new technologies, frameworks, and industry best practices—proactively applying improvements to code quality and team workflows.
• Experience: At least 4 years of hands‑on experience in a backend or data engineering capacity, preferably in a product‑driven environment.
• Education (Preferred): Bachelor's degree in Computer Science, Engineering, or a related technical field.

As set forth in Media Lab.

AI Inc.’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.