Database Engineer

About Crunchyroll

Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We super-serve over 100 million anime and manga fans across 200+ countries and territories, and help them connect with the stories and characters they crave. Whether that experience is online or in-person, streaming video, theatrical, games, merchandise, events and more, it’s powered by the anime content we all love.

Join our team, and help us shape the future of anime!

About the role

Crunchyroll is growing and changing, presenting unique challenges and opportunities to support millions of anime fans around the world. The Data Engineering team provides seamless help to our internal stakeholders, ensuring an exceptional experience for all Crunchyroll fans.

As a Database Engineer for the Data Engineering team, you will be responsible for maintaining and enhancing the reliability of our data infrastructure. Your work will directly impact the availability and performance of our data services, enabling the organization to make data-driven decisions. You will collaborate closely with data engineers, and software engineers to develop and drive 100% automation, best practices for deep monitoring and alerting.

Key Areas of Responsibility

• Database Strategy & Technical Leadership: Act as the strategic subject matter expert for database engine best practices, storage engines, and long-term data placement strategy across the broader engineering organization. Partner with tech leadership to raise the collective database expertise of the team.
• SQL Optimization & Application Performance: Drive deep application performance analysis. Own the identification, debugging, and elimination of query execution bottlenecks, optimizing raw SQL, missing indexes, execution plans, and data models to maximize throughput and minimize latency.
• Cloud Database Architecture & Scale: Design, scale, and evaluate schemas leveraging AWS-native database services, including Amazon RDS, Aurora (MySQL/PostgreSQL), and NoSQL engines (DynamoDB), ensuring systems adhere strictly to rigorous scalability benchmarks.
• Database Internals & Systems Analysis: Execute deep-dive performance forensics into database engine behaviors, memory structures, replication lag, locking mechanisms, and OS/hardware saturation metrics (such as Disk/IO performance) to preemptively address platform degradation.
• Engineering Mentorship & Advisory: Partner closely with internal application development and data teams to review data access patterns, optimize application-level database interaction layers, and establish organizational standards around indexing and schema configurations.