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 our API, managing everything from data streaming and storage to analytics features at petabyte scale.
You will lead building the data platform for the long-term vision. You’ll not only design and deliver complex systems, but also drive technical strategy, set architectural direction, and influence how the data platform evolves. You’ll partner closely with product, engineering teams, and leadership to ensure we’re building the right abstractions and reusable components that scale with our growth. You know when to slow down to build the right solution vs. work against time. This is a role with broader ownership, where your leadership and judgment will raise the technical bar across the team and directly impact how customers succeed with high-volume telematics data.
Own projects aimed at enhancing data storage, replication, 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 petabytes of IoT and time-series data.
Develop and maintain real-time data systems to ingest growing data volumes.
Implement distributed tracing, data lineage and observability patterns to improve monitoring and troubleshooting.
Manage infrastructure that powers the current and future services, ensuring scalability, reliability, and zero downtime for HA services.
Write clean, maintainable code in Java and Python for various platform components.
Shape architectural decisions to ensure scalability and reliability throughout the data platform.
6+ years of experience in platform engineering or data engineering.
4+ years of experience designing and optimizing data pipelines at TB to PB scale.
Proficient in Java, with a focus on clean, maintainable code.
Strong system design skills with a focus on big data and real-time workflows.
Experience with lake-house architectures (e.g., Iceberg, Delta, Paimon).
Experience with real-time data processing tools like Kafka, Flink and Spark.
Knowledge of distributed systems and large-scale data challenges.
Strong problem-solving skills and a collaborative mindset.
Note: You don't need to check every box. Java experience is strongly preferred, but if you're confident you can pick it up quickly, we're open to that. Same goes for other competencies on this list.
Experience working with orchestration / workflow engines (e.g. Step Functions, Temporal)
Experience with serverless and/or event-driven architectures (e.g. AWS Lambda, SQS).
Experience with Javascript/Typescript languages (for cross team work)
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
Staff Software Engineer, Data Platform • Toronto, Ontario, USA
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