Senior Data Engineer, Event Data
<img src="https://app.gurulink.ca/img/gl_logo_112x112.jpg" border="0"><br><br><b>Location:</b> REMOTE / Toronto, Ontario - Canada<br><b>Job Type:</b> Permanent<br><br><b>Description:</b><p>We’re working with an established technology company that is building out a new Event Data team and looking for a Senior Data Engineer to help design and develop the systems responsible for ingesting, processing, and serving extremely large volumes of event data.<br><br>This is a hands-on senior engineering role focused on large-scale streaming and event-driven data systems. You’ll work across event ingestion, stream processing, analytical data stores, data modeling, system migrations, and production operations while helping establish the architecture and engineering practices for a newly formed team.<br><br>The environment operates at billions-of-events scale, making this a strong opportunity for an engineer who has worked with high-volume streaming systems and enjoys solving complex data infrastructure problems.<br><br>What You’ll Do<br><br>- Design, build, and maintain high-volume event streaming pipelines that ingest data from external systems, internal services, and third-party sources.<br>- Build systems capable of reliably processing and serving event data at billions-of-events scale.<br>- Develop and operate analytical databases and data models optimized for high-volume queries and low-latency access.<br>- Build production services and pipeline components using Python and/or Elixir.<br>- Work with stream-processing technologies and message brokers such as Apache Flink, Kafka, Pulsar, or Kinesis.<br>- Integrate existing event pipelines with modern streaming infrastructure and design migration strategies that minimize disruption to downstream systems.<br>- Build monitoring, alerting, and observability around event pipelines, including data freshness, pipeline health, SLAs, and production reliability.<br>- Define and maintain event schemas, data contracts, and data-quality standards.<br>- Collaborate with data platform, product engineering, analytics, and other technical teams that produce or consume event data.<br>- Participate in architecture and system-design discussions while helping establish engineering standards and best practices for the team.<br>- Help operationalize the platform through infrastructure automation, documentation, runbooks, and production support.</p><br><b>Must Have skills:</b><p>What We’re Looking For<br><br>- 6+ years of professional experience in data engineering, backend engineering, systems engineering, or a closely related area.<br>- Significant hands-on experience building event-driven, streaming, or high-volume data systems.<br>- Strong proficiency with Python and/or Elixir for building production services, application connectors, data-processing components, or pipelines.<br>- Advanced SQL skills, including data modeling, query optimization, and analytical workloads.<br>- Production experience with columnar or OLAP databases and large analytical datasets.<br>- Strong experience with streaming technologies and message brokers such as Apache Flink, Kafka, Pulsar, or Kinesis.<br>- Experience designing systems that process large volumes of events or messages with requirements around throughput, latency, reliability, and availability.<br>- Experience migrating or integrating legacy systems with newer distributed or streaming architectures.<br>- Strong production engineering experience, including monitoring, alerting, observability, SLA/SLO management, dashboards, and runbooks.<br>- Experience designing and operating cloud-based data infrastructure, particularly on AWS. GCP experience is also valuable.<br>- Experience with Infrastructure-as-Code tooling such as Terraform or CloudFormation.<br>- Ability to contribute meaningfully to system design and architecture discussions and communicate technical trade-offs clearly across engineering teams.</p><br><b>Nice to have skills:</b><p>Nice to Have<br><br>- Hands-on Apache Flink experience.<br>- Experience with Databricks.<br>- Experience with multiple messaging or streaming platforms such as Kafka, Pulsar, or Kinesis.<br>- Experience working with retail, ecommerce, marketing, clickstream, purchase, or product-interaction event data.<br>- Experience building data platforms where event data needs to be consumed by multiple downstream products, analytics systems, or engineering teams.<br>- Experience working with data systems operating at billions-of-events scale.<br><br>The base pay range for this position is $145k CAD - $185k CAD</p><br><b>Job Function:</b> Data Engineer<br><br><br>