Staff Data Platform Engineer (Streaming Platform)

Toronto, ON
On-site
Posted Oct 15, 2026
1 position

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Employment type: Full-time
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Own the development of platform capabilities for data replication, storage, enrichment, reporting, and scalable streaming and batch pipelines. Design petabyte-scale storage and real-time ingestion systems, and implement data lineage, distributed tracing, and observability.

Job details

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

What you’ll do

Requirements

Requires 8+ years of platform or data engineering experience and 6+ years designing and optimizing data pipelines at terabyte-to-petabyte scale. Candidates should have strong Java skills, big data and real-time system design expertise, and experience with lakehouse and streaming technologies such as Iceberg or Delta and Kafka, Flink, or Spark.