Data Engineer, Event Data

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer, Event Data based in Canada.

This is an opportunity to join a newly established data engineering team building the infrastructure behind high-volume client and internal event data.

You will design systems that ingest, process, transform, and serve billions of events with a strong focus on speed, reliability, and availability.

The role combines modern streaming technologies, analytical databases, and production software engineering using Elixir and Python.

You will help shape the architecture of a critical data domain while influencing how event data moves throughout the wider platform.

Working across data, product engineering, and analytics teams, you will turn complex data requirements into dependable event data products.

The environment offers significant technical ownership, with opportunities to establish engineering standards and best practices from the ground up.

This is a remote position in Canada with a strong emphasis on scalable systems, operational excellence, and collaborative technical problem-solving.

Accountabilities:

• Design, build, and maintain scalable event-streaming pipelines that ingest data from client systems, internal services, and third-party sources.
• Develop and operate analytical databases and data models optimized for high-volume event workloads, efficient querying, and low-latency data access.
• Build production-grade services in Elixir and/or Python for event processing, transformation, routing, and integration.
• Integrate legacy event pipelines with modern streaming infrastructure, designing migration strategies that reduce risk and minimize disruption for downstream consumers.
• Establish and maintain monitoring, alerting, observability, and operational tooling to ensure pipeline health, data freshness, reliability, and SLA compliance.
• Define and enforce event schemas, data contracts, and data-quality standards in collaboration with teams that produce and consume event data.
• Partner with data platform, product engineering, and analytics teams to understand requirements and deliver reliable, scalable event data products.
• Participate in architecture and system design reviews, contributing to technical decisions and establishing best practices for event-data engineering.
• Develop and maintain infrastructure using Infrastructure-as-Code approaches, supporting reliable and repeatable deployment of data systems.
• Contribute to operational documentation, runbooks, and production processes that enable dependable management of large-scale event data systems.

Requirements:

• Strong proficiency in Elixir and/or Python, with experience building application connectors, data services, processing components, or production pipeline infrastructure.
• Advanced SQL skills, including data modeling, query optimization, and analytical workloads.
• Hands-on experience operating columnar or OLAP databases in production at significant scale.
• Practical experience with stream-processing frameworks and message brokers such as Apache Flink, Kafka, Pulsar, or Kinesis; Flink experience is particularly valuable.
• Demonstrated ability to integrate and migrate systems across legacy and modern architectures while managing technical and operational risk.
• Proven experience operationalizing production data pipelines, including monitoring, alerting, SLA dashboards, runbooks, and incident-response practices.
• Experience designing and operating data systems on AWS; GCP experience is an advantage.
• Experience with Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or comparable technologies.
• Strong understanding of scalable event-data architectures and production reliability.
• Excellent collaboration and communication skills, with the ability to lead design discussions, write clear technical specifications, and work effectively across engineering and data teams.
• Experience working with retail or customer-event data, such as clickstream, purchase, or product-interaction events, is a plus.
• Familiarity with Databricks, Flink, Kafka, Pulsar, or Kinesis is an additional advantage.
• Ability to take ownership in a newly formed team and contribute to architectural decisions, engineering standards, and long-term technical direction.

Benefits:

• CAD $130,000-$165,000 base salary range, depending on job-related knowledge, skills, and experience.

• Potential additional bonus, depending on the position ultimately offered.
• Comprehensive medical, financial, and other benefits.

• Remote work opportunity in Canada.

• Opportunity to join a newly formed team and help shape the architecture of a critical data platform from the ground up.
• Exposure to modern streaming, analytical database, cloud, and distributed data technologies at billions-of-events scale.
• Significant technical ownership and opportunities to influence engineering standards and best practices.
• Collaborative environment with close interaction across data platform, product engineering, and analytics teams.
• Inclusive workplace committed to creating an environment where people from diverse backgrounds can thrive.
• Equal opportunity employment and consideration for candidates with diverse experiences and perspectives.