Principal Data Engineer

Digital Extremes•London, ON

9h•CA$115,000 - CA$125,000•Onsite

About The Position

We are seeking a Principal Data Engineer with extensive experience in data infrastructure to join our team. Unlike many modern roles that rely entirely on cloud-managed services, this position is looking for someone to manage our self-hosted and on-premise data stacks. We need a proactive, solutions-oriented engineer who can rapidly master our current self-hosted systems, identify performance bottlenecks, and design our future infrastructure to adapt to the company needs. In this role, you will own the technical architecture, set engineering standards, and translate complex business requirements into reliable, scalable data systems.

Requirements

5+ years of professional experience in data engineering, database administration, or backend infrastructure, with a strong, proven focus on managing self-hosted/on-premise environments rather than exclusively cloud-managed services.
Extensive hands-on experience managing and optimizing database management systems, specifically PostgreSQL and MongoDB (both relational and NoSQL ecosystems).
Proven experience setting up, maintaining, and tuning self-hosted/on-premise databases and data warehouses.
Strong proficiency in SQL and deep comfort working within Linux/Unix environments (command line, shell scripting, system performance tuning).
Hands-on experience with modern ETL orchestration tools such as Dagster or Airflow.
In-depth knowledge of core data warehousing concepts and relational data modeling.
Proven track record of owning complex technical systems, driving implementation, and ensuring architectural standards are met.
Ability to clearly communicate technical decisions, trade-offs, and infrastructure constraints to both engineering teams and non-technical stakeholders.
Applicants must be legally eligible to work in Canada at the time of application.

Responsibilities

Manage and optimize self-hosted database and data warehousing solutions. Oversee performance tuning, hardware planning, and OS-level monitoring for large-scale data systems.
Design, develop, and maintain robust ETL/ELT pipelines for data ingestion and processing from varied, complex data sources.
Drive large-scale technical projects from design to delivery, making key architectural decisions and managing technical risk.
Establish code and architecture review standards, championing engineering best practices across the team.
Ensure infrastructure and pipelines strictly comply with government policies, data privacy, and GDPR regulations.
Partner with data scientists, analysts, and business stakeholders to translate complex data requirements into scalable infrastructure.