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 students able to relocate to Toronto/GTA for the full term

About the role

We're looking for an engineer who's excited about building scalable data platforms and learning how to tackle complex backend challenges. This is an opportunity to work on real production systems, contributing to the data platform that powers Terminal's API and handles everything from data streaming and storage to analytics at petabyte scale.

You'll work closely with our senior software engineers, contributing to projects that directly impact how we process and deliver high-volume telematics data to our customers. This is a hands-on role where you'll gain exposure to production systems, modern data engineering tools, and large-scale distributed architectures.

What you will do

• Contribute to projects focused on data replication, storage, enrichment, and reporting capabilities
• Help build and optimize streaming and batch data pipelines that support our core product and API
• Work on scalable storage solutions for handling petabytes of IoT and time-series data
• Assist in developing and maintaining real-time data systems to ingest growing data volumes
• Support implementation of distributed tracing, data lineage and observability patterns
• Participate in code reviews and learn best practices for writing clean, maintainable code in Java and Python
• Collaborate with cross-functional teams to understand requirements and deliver solutions
• Gain hands-on experience with modern data infrastructure and cloud technologies

The ideal student will have

• Availability for co-op/internship of at least 6 months full-time and on-site at our Toronto office
• Strong programming fundamentals in Java or Python (or demonstrated ability to learn quickly)
• Understanding of data structures, algorithms, and system design basics
• Coursework or project experience with databases, distributed systems, or data processing
• Curiosity about large-scale data systems and real-time processing
• Strong problem-solving skills and eagerness to learn
• Ability to work collaboratively in a team environment
• Nice-to-have:
  • Currently pursuing a Master’s degree in Computer Science or a related field
  • Prior internship or co-op experience
  • Personal or academic projects involving data pipelines or stream processing
  • Exposure to cloud platforms (AWS, GCP, or Azure)
  • Familiarity with SQL and database concepts
  • Interest in or exposure to technologies like Kafka, Flink, Spark, or similar

Tech stack (you'll learn and work with):

• Languages: Java, Python
• Framework: Springboot
• Storage: AWS S3, AWS DynamoDB, Apache Iceberg, Redis
• Streaming: AWS Kinesis, Apache Kafka, Apache Flink
• ETL: AWS Glue, Apache Spark
• Serverless: AWS SQS, AWS EventBridge, AWS Lambda and Step Functions.
• Infrastructure as Code: AWS CDK
• CI/CD: GitHub Actions

Benefits

• Strong compensation, paid time off + statutory holidays
• Brand new MacBook and computer equipment
• 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.