Software Engineer, Data Platform

Reposted 22 Days Ago
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Toronto, ON, CAN
Hybrid
200K-295K Annually
Senior level
Information Technology • Logistics • Software • Transportation
The Role
Lead design and implementation of a scalable data platform handling petabytes of telematics and time-series data. Build and optimize streaming and batch pipelines, design storage solutions, implement observability and data lineage, manage HA infrastructure, and write maintainable Java/Python code while shaping long-term architectural strategy.
Summary Generated by Built In
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
  • Languages: Java, Python; TypeScript and Node.js is also used across Terminal

  • Framework: Spring Boot

  • Storage: AWS S3, Postgres, DynamoDB, Apache Doris, Apache Iceberg, Redis

  • Streaming: AWS Kinesis, Apache Kafka, Apache Flink

  • Orchestration: Temporal, Step Functions

  • ETL: AWS Glue, Apache Spark

  • AI: LangGraph, Deep Agents, Bedrock

  • IaC: Pulumi

Compensation

We hire for this role at two levels and calibrate to where you come in. All compensation is base salary plus meaningful equity.

  • Senior: base $200,000 to $255,000 + equity

  • Staff: base $235,000 to $295,000 + equity

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.

The interview process
  1. Intro call with the CTO (30 min)

  2. Virtual system design (60 min)

  3. On-site technical loop (120 min)

  4. On-site culture loop + final (180 min)

Accessibility and accommodation

Terminal is committed to an accessible hiring process. If you need an accommodation at any stage — applying, interviewing, or completing an assessment — email [email protected] and we will work with you to meet your needs. Accommodations are available under the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code, and requesting one will never affect how your application is considered.

Skills Required

  • 6+ years of experience in platform engineering or data engineering
  • 4+ years designing and optimizing data pipelines at TB to PB scale
  • Proficient in Java and able to write clean, maintainable code
  • Experience writing production code in Python
  • Strong system design skills focused on big data and real-time workflows
  • Experience with lake-house architectures (e.g., Apache Iceberg, Delta, Paimon)
  • Experience with real-time data processing tools (Apache Kafka, Apache Flink, Apache Spark)
  • Knowledge of distributed systems and large-scale data challenges
  • Experience building and optimizing streaming and batch data pipelines
  • Experience managing infrastructure for scalable, reliable, high-availability services
  • Familiarity with AWS storage and data services (S3, DynamoDB, Kinesis, Glue, SQS, EventBridge, Lambda, Step Functions, CDK)
  • Experience with orchestration/workflow engines (e.g., Step Functions, Temporal)
  • Experience with serverless and event-driven architectures (e.g., AWS Lambda, SQS)
  • Experience with Javascript/Typescript for cross-team work
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The Company
161 Employees
Year Founded: 2017

What We Do

Terminal provides a Universal API for Telematics and ELDs, simplifying the integration of telematics data into applications. By offering a single, normalized API for vehicles, drivers, and locations, Terminal helps fleet management, carrier TMS, digital brokerage, and insurance companies accelerate their product development and focus on core features, significantly increasing their innovation velocity and ability to onboard new customers quickly.

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