Senior Engineer, Data Platform

Location: Toronto, Canada (Remote)

Salary: CAD 145,000–185,000 per year, with potential additional bonus and benefits.

Company

hirify.global scales content personalization for marketers through data-activated content generation and AI decisioning, serving global brands from operations across North America, Central America, Europe, Australia, and Japan.

What you will do

• Design and deliver data ingestion pipelines and supporting infrastructure.
• Migrate legacy data lifecycle management to the unified data platform without disrupting existing data consumers.
• Establish SLIs and SLOs, dashboards, alerting, monitoring, observability, and incident response for data pipelines and services.
• Build flexible storage layers for transactional, analytical, and machine learning workloads.
• Collaborate with product engineering, analytics, and machine learning teams on data contracts, requirements, and standards.
• Design semantic metadata and multi-tenant data models supporting secure data sharing, isolation, governance, and compliance.

Requirements

• Deep understanding of data governance and data lifecycle management, including data quality, lineage, retention, and access control.
• Production-scale experience with OLAP and OLTP systems, SQL optimization, and data warehouse technologies such as Databricks, ClickHouse, or Redshift.
• Experience designing and operating data systems on AWS and working in multi-cloud environments; GCP experience is a plus.
• Proficiency with Docker, Kubernetes, and Infrastructure-as-Code tools such as Terraform or CloudFormation.
• Experience integrating legacy platforms with modern architectures through well-designed interfaces and migration strategies.
• Ability to lead system design discussions, write technical specifications, document architectural decisions, and collaborate across teams.

Nice to have

• Familiarity with Elixir for concurrent and fault-tolerant data services.
• Experience with Airflow, Kafka, Apache Flink, or similar data pipeline and streaming technologies.
• Hands-on experience with columnar and OLAP databases such as Databricks or ClickHouse.

Culture & Benefits

• Medical, financial, and other benefits are provided.
• Work takes place in a diverse and inclusive environment.
• Collaboration spans engineering, analytics, infrastructure, product, and machine learning teams.