About the Role
Fivetran is building data pipelines to power the modern data stack for thousands of companies.
We're seeking an enthusiastic Software Engineer to join our fast-growing data company. As a part of the databases team, you will help drive performance improvements, improve reliability/architecture and build new features for our NoSQL data pipeline services.
This is a full-time, hybrid position based out of Fivetran's Toronto, Canada office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team
Technologies You'll Use
Java
MongoDB, Amazon DynamoDB, Azure Cosmos DB
AWS, GCP, Azure
Bazel, Docker, Kubernetes, Github
What You'll Do
Write and deliver code reliably, along with automated tests (unit and integration)
Optimize code to make it more performant
Break down project work into tasks with estimates
Give and receive feedback through code reviews
Collaborate daily with team members to develop new features and improvements while minimizing technical debt
Resolve customer issues in collaboration with customer support
Work across the software development lifecycle: requirements, design, prototype, implementation, review, release, and monitoring
Use AI coding agents to automatically generate code for use cases such as incident resolution, feature development, testing, and investigations
Skills We're Looking For
Expertise in Java development
Experience developing reliable software with high-volume data management under strict SLAs
Experience working with popular cloud platforms (e.g. AWS, GCP, Azure)
Experience using AI coding agents for development
Knowledge of popular NoSQL databases (e.g. MongoDB, Amazon DynamoDB)
Knowledge of and appreciation for clean code practices
Ability to troubleshoot problematic code and identify root cause(s)
Optional Bonus Skills?
Experience working with MongoDB and/or Amazon DynamoDB change data capture
Experience developing data integration tools (ETL or ELT)
Experience identifying and optimizing performance bottlenecks in distributed systems
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