Staff Data Platform Engineer
1 day ago
Toronto, ON, Canada
TekRek
Full-time
Free with email or Google
Save this job and keep your search organized
Create a free account to save jobs, create alerts and return to this listing from your dashboard.
Free with email or Google
By continuing, you agree to our Terms & Privacy Policy.
The Role
TekRek is partnered with a high-growth product company building the data platform behind a modern telematics API, supporting real-time ingestion, storage, enrichment, and analytics for high-volume IoT and time-series workloads at petabyte scale.
This is not a traditional data engineering seat; you will own the long-term buildout of the data platform powering the API and analytics layer, drive architectural direction, and partner with product, engineering, and leadership to deliver scalable abstractions and reusable components.
What You'll Do
Own projects enhancing data replication, storage, enrichment, and reporting capabilities
Build and optimize streaming and batch pipelines that support the core product and API
Design scalable storage solutions for petabytes of IoT and time-series data
Develop and maintain real-time ingestion systems to support growing data volumes
Implement distributed tracing, data lineage, and observability to improve monitoring and troubleshooting
What You Bring (Must Have)
8 plus years of experience in platform engineering or data engineering
6 plus years designing and optimizing data pipelines at TB to PB scale
Strong Java proficiency with a focus on clean, maintainable production code
Strong system design skills for big data and real-time workflows
Experience with lakehouse and streaming ecosystems such as Iceberg or Delta, plus Kafka or Flink or Spark
Languages: Java, Python
Framework: Spring Boot
Streaming: AWS Kinesis, Kafka, Flink
ETL: AWS Glue, Spark
Serverless: SQS, EventBridge, Lambda, Step Functions
This is not a traditional data engineering seat; you will own the long-term buildout of the data platform powering the API and analytics layer, drive architectural direction, and partner with product, engineering, and leadership to deliver scalable abstractions and reusable components.
What You'll Do
Own projects enhancing data replication, storage, enrichment, and reporting capabilities
Build and optimize streaming and batch pipelines that support the core product and API
Design scalable storage solutions for petabytes of IoT and time-series data
Develop and maintain real-time ingestion systems to support growing data volumes
Implement distributed tracing, data lineage, and observability to improve monitoring and troubleshooting
What You Bring (Must Have)
8 plus years of experience in platform engineering or data engineering
6 plus years designing and optimizing data pipelines at TB to PB scale
Strong Java proficiency with a focus on clean, maintainable production code
Strong system design skills for big data and real-time workflows
Experience with lakehouse and streaming ecosystems such as Iceberg or Delta, plus Kafka or Flink or Spark
Languages: Java, Python
Framework: Spring Boot
Streaming: AWS Kinesis, Kafka, Flink
ETL: AWS Glue, Spark
Serverless: SQS, EventBridge, Lambda, Step Functions