Senior/Staff Software Engineer, Data Platform

About Terminal Terminal builds telematics data infrastructure for the commercial fleet industry. Commercial auto insurers and fleet software companies, including industry leaders like Intact Insurance, depend on our platform to access GPS, speeding, and vehicle data from 330+ telematics providers. We recently raised our Series A led by Battery Ventures and are backed by Y Combinator, Golden Ventures, Penske Transportation Solutions, and Intact Private Capital. Our team works together in person in Toronto, combining early-stage speed with late-stage maturity while processing many terabytes of vehicle data every day.

For more on working at Terminal, see our careers page at withterminal.com/careers.

Note that this role is only open to Toronto/GTA-based candidates.

About The Role We’re looking for an engineer who thrives on building scalable platforms and enjoys tackling hard data and backend challenges. This isn’t a data engineering role: you’ll design and optimize the data platform that powers Terminal’s unified API, owning everything from streaming and storage to analytics, and moving terabytes of IoT and time-series data per day. It’s core systems engineering, and you’ll work across both data and backend to build the critical systems that drive the product’s data flows end to end.

You’ll partner with engineering teams and customers to build the right abstractions and reusable components that scale with our growth, help set architectural direction, and shape how the platform evolves. You know when to slow down to build the right thing versus ship a fast experiment. This is a role with real ownership, where your judgment raises the bar for the team and directly shapes how customers succeed with high-volume telematics data.

What You’ll Do

• Design and build the streaming and batch pipelines (replication, analytics, and enrichment), that feed the product and API.
• Build the storage systems that need to scale to petabytes of time-series data and stay fast under load.
• Improve the primitives the platform runs on: data quality, lineage, stream/batch processing, and the high-availability infrastructure enterprise customers depend on.
• Shape how we build, not just what we build: the AI-powered tooling that lets the platform increasingly improve itself.
• Work on open source technologies, contributing back when we see the opportunity.
• Make the architectural calls that keep the platform ahead of its scale.
• Work day to day in Java and Python.

What We’re Looking For

• A strong engineer who’s built and owned production platforms or distributed systems at real scale, and can drive an architecture to done without being managed.
• Writes clean, maintainable code with a solid computer science foundation.
• Hands-on experience with big-data frameworks, building streaming or batch systems that stay correct and fast as data grows from TB to PB.
• Depth in distributed systems: you anticipate failure modes and design for them up front.
• Platform builder: you make the systems other teams stand on, and design them to last.
• Sound judgment in ambiguity: you scope before building and know when to go deep on details VS ship fast experiments.
• Strong in Java or another JVM language (Scala, Kotlin), or confident to pick it up fast.

The ideal candidate brings deep experience with data streaming and processing (Kafka, Flink, Spark, warehouses, lakehouses), though it isn’t required. Strong platform, distributed-systems, or backend engineers who’ll ramp into the data side are welcome.

You don’t need to check every box. If you’re missing some but confident you’ll close the gap quickly, apply anyway.

Nice to have

• Open source contributions (especially relating to data processing and storage)
• Lakehouse storage (Iceberg, Delta, Paimon, Doris).
• Orchestration and workflow engines (Temporal, Step Functions).
• Time-series and spatial (spatio-temporal) data.

How We Work

• In person 4 days/week, downtown Toronto. We build better together in a room.
• High ownership. Everyone takes projects end-to-end and helps shape the product.
• Platform thinking. Our work is the foundation that other teams build products on. We design capabilities that compose into features and accept complexity so others don’t have to.
• Talk to customers. Whether it’s a paying customer or an internal team, we talk to our customers to understand their problems before we ship solutions.

**Tech stack…