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Staff Data Platform Engineer (Streaming Platform)

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Onsite

Staff Data Platform Engineer (Streaming Platform)

TekRek

Staff Data Platform Engineer (Streaming Platform)

Skills

Big DataData EngineeringDynamoDBPythonJavaSpring BootKafkaRedisData AnalysisAWSGitHubAWS Kinesis

8 days ago

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Important information


Contract type:

Permanent

Location:

Toronto, ON, Canada

Work mode:

Onsite

Published on:

15 October 2026

What they need


About the Company

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.

The Role

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

Tech Stack

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

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