
Software Engineer II - Performance Engineering
- Oakland, CA
- Permanent
- Full-time
- Java17, JUnit5
- Docker and Kubernetes
- AWS, GCP, Azure
- RDBMS and NoSQL Databases
- New Relic
- Terraform
- Bazel
- Develop and Debug code to identify and fix performance issues
- Analyze production workloads and system performance metrics to identify performance bottlenecks in our system
- Design, develop and maintain performance benchmarks
- Build proof of concepts and translate successful ones into solutions to maximize Fivetran product's performance and efficiency
- Build and maintain a platform that focuses on improving the performance, resilience and quality of Fivetran products
- Impact Fivetran business across product verticals through the work you do
- Develop deep expertise in Fivetran's Product, Infrastructure, and Platform
- Communicate, coordinate, and align strategy with the engineering team members; make recommendations to improve reliability, performance, best practices, and processes
- Work with cross-functional teams (Developers, Product, SRE) across the organization
- Actively engage with fellow engineers in design and code reviews to ensure we deliver performant solutions that improves the product's efficiency
- 2+ years of experience in the software industry with a passion for solving complex software engineering problems
- Software engineering foundation - experience designing and developing reusable libraries and experimentation platforms for backend and frontend from scratch leveraging industry best practices
- Strong knowledge of and experience with OOP, preferably Java
- Hands-on experience working with any cloud technologies(AWS, GCP, Azure) and containerization methodologies like Docker, K8s
- Experience working with RDBMS or NoSQL databases
- Experience interacting with continuous integration tools like CircleCI/Jenkins
- Knowledge of observability tools like New Relic, Splunk, DataDog is a plus
- Knowledge of Data Engineering is a plus
- Performance Engineering background - experience analyzing, troubleshooting and automating performance workloads on large scale systems