Terminal is Plaid for Telematics in commercial trucking. Companies building the next generation of insurance products, financial services, and fleet software for trucking use our Universal API to access GPS data, speeding data, and vehicle stats.

We are a fast growing, venture-backed startup supported by top investors including Y-Combinator, Golden Ventures, and Wayfinder Ventures. Our exceptionally talented team is based in Toronto, Canada.

For more information, check out our website https://withterminal.com

About Terminal

Terminal is Plaid for Telematics in commercial trucking. Companies building the next generation of insurance products, financial services and fleet software for trucking use our Universal API to access GPS data, speeding data and vehicle stats.

We are a fast-growing, venture-backed startup supported by top investors including Y Combinator, Golden Ventures and Wayfinder Ventures. Our exceptionally talented team is based in Toronto, Canada.

For more info, check out our website: https://withterminal.com

Note: This role is only available to Toronto/GTA-based candidates

About the role

We’re looking for an engineer who thrives on building scalable data platforms and enjoys tackling complex backend challenges. This isn’t just a data engineering role—you’ll be designing and optimizing the data platform that powers Terminal’s API, managing everything from data streaming and storage to analytics features at terabyte scale and beyond.

You should be comfortable navigating both data and backend engineering, with a solid foundation in software development. You’ll work with advanced data architectures, including Iceberg, Flink, and Kafka, tackling large-scale challenges and contributing to core product development using Java and Node.js. If you’re excited by the opportunity to shape a high-impact platform and tackle diverse engineering problems, we’d love to hear from you.

What you will do:

• Own projects aimed at enhancing data replication, storage, enrichment, and reporting capabilities.
• Build and optimize efficient streaming and batch data pipelines that support our core product and API.
• Design scalable storage solutions for handling terabytes of IoT and time-series data.
• Develop and maintain real-time data systems to ingest growing data volumes.
• Implement distributed tracing and observability patterns to improve monitoring and troubleshooting.
• Write clean, maintainable code in Java and Node.js for various platform components.
• Shape architectural decisions to ensure scalability and reliability throughout the data platform.

The ideal candidate will have:

• 3+ years of experience in platform engineering or data engineering.
• 2+ years of experience designing and optimizing data pipelines at TB to PB scale.
• Strong system design skills with a focus on data workflows.
• Familiarity with lake-house architectures (e.g., Iceberg, Delta, Hudi, Snowflake).
• Experience with real-time data processing tools like Kafka, Spark and Flink.
• Knowledge of distributed systems and large-scale data challenges.
• Proficient in Java, with a focus on clean, maintainable code.
• Strong problem-solving skills and a collaborative mindset.

Tech Stack

• Languages: JavaScript / TypeScript, Java
• Infrastructure as Code (IaC): SST, AWS CDK
• Cloud Services:
  • Compute and Orchestration: AWS Lambda, AWS Step Functions
  • Storage: Amazon S3, Amazon DynamoDB
  • Messaging and Events: Amazon SQS, Amazon EventBridge
• Data Processing: AWS Glue, Apache Flink, Kafka, Iceberg, DuckDB
• CI/CD: GitHub Actions

Benefits

• Strong compensation and equity packages
• Brand new MacBook and computer equipment
• Top-tier health/dental benefits and a flexible healthcare spending account
• Personal spending account for professional development, fitness and wellness
• Four weeks paid time off + statutory holidays
• In-person culture with an office located in downtown Toronto

• AWS serverless architecture: Lambda, DynamoDB, S3, SQS, EventBridge and Step Functions.
• End-to-end TypeScript: SST framework, Next.js and Tailwind.
• Infrastructure as Code: SST and CDK.
• CI/CD: GitHub Actions and SEED.