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TekRek

Staff Data Platform Engineer (Streaming Platform)

Toronto, ON, Canada

Full-time

Within 25 km of Vaughan · About 22.9 km from the city centre

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Job details

Job type: Full-time
Apply by: Nov 13, 2026
Posted: Oct 14, 2026

Original job description

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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More about this job

Responsibilities

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.

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.

Skills

Java
Python
Data Platform Engineering
Data Engineering
Streaming Pipelines
Batch Pipelines
Big Data System Design
Real-Time Data Ingestion
Data Replication
Lakehouse Architecture
Apache Iceberg
Delta Lake
Kafka
Flink
Spark
Distributed Tracing

Visa sponsorship

Not detected in the job text

Keywords

Java
Python
Spring Boot
AWS S3
DynamoDB
Apache Iceberg
Delta Lake
Redis
AWS Kinesis
Kafka
Flink
Spark
AWS Glue
SQS
EventBridge
AWS Lambda
Step Functions
AWS CDK
GitHub Actions
Data Platform Engineering
Data Pipelines
Streaming
Batch Processing
Real-Time Ingestion
Petabyte-Scale Storage
IoT Data
Time-Series Data
Data Lineage
Distributed Tracing
Observability

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