Data Platform Engineer

Tucows Inc.

9h•CA$90,700 - CA$113,400•Remote

About The Position

We’re looking for a curious, technically strong, and automation-minded Data Platform Engineer to join our Data Engineering team. This is a high-impact platform engineering role for someone who enjoys building reliable systems, writing maintainable automation, and helping data teams move faster, more safely, and with more confidence. You’ll work at the intersection of data engineering, business intelligence, finance analytics, cloud infrastructure, governance, and AI-enabled decision support. What we’re really hiring for is strong engineering fundamentals, comfort with ambiguity, and the drive to apply those fundamentals across different systems. We’re hiring an engineer who can pick up infrastructure work, governance work, or pipeline work as needed and help turn knowledge that currently lives in repos, configs, and people’s heads into durable platform practices. There will be a lot to learn here, even if you arrive experienced. That’s the appeal, not the catch.

Requirements

3+ years in data engineering, software engineering, DevOps, platform engineering, or a related technical role.
Hands-on experience operating workloads in AWS or another major cloud provider, with a solid grasp of IAM, networking, compute, managed services, deployment patterns, and day-to-day cloud operations.
Proficiency in Python for automation, internal tooling, platform workflows, or data engineering support.
Working knowledge of SQL. Advanced SQL is a plus, but not a prerequisite.
Hands-on experience with Terraform or another infrastructure-as-code tool, including code review, state-aware changes, environment management, and safe deployment practices.
Comfortable using Git-based development workflows, pull requests, automated testing, and CI/CD pipelines to ship changes safely.
Good working knowledge of Kubernetes and container-based deployments. You should be comfortable understanding deployments, pods, services, logs, configuration, and common failure modes. Experience with EKS is especially valuable.
Skilled at using logs, metrics, and alerts to investigate failing systems, reason through incomplete information, and identify likely root causes.
Familiarity with RBAC, IAM, least-privilege access, or governance controls in at least one platform — cloud, warehouse, BI, or application-level systems.
Attention to detail, curiosity, good judgment, and genuine eagerness to learn unfamiliar tools and systems.
Experience working with vendor support, production incidents, severity-based escalation, and operational follow-through.
Willingness to participate in on-call and after-hours support as needed. You understand that reliable platforms require thoughtful operations, not just build work.
Clear written communication and the ability to work effectively with engineers, analysts, and data stakeholders in a remote-first team.

Nice To Haves

Experience with GCP, OpenStack, Helm, Snowflake, BigQuery, dbt, Airflow/MWAA, Kafka, DataHub, Fivetran, Stitch, Pentaho Data Integration, Prometheus, Grafana, CloudWatch, Looker, GitHub, Claude Code.

Responsibilities

Keep the data platform healthy: Monitor infrastructure and pipelines, respond to issues, troubleshoot failures from logs and metrics, and help identify root causes so we can prevent repeat problems.
Make infrastructure changes safely: Build, review, and deploy infrastructure through code using Terraform, AWS, Kubernetes or container-based deployment patterns, and CI/CD workflows.
Improve automation and tooling: Write Python, bash, and CI/CD automation that reduces manual toil, improves reliability, and makes common platform tasks safer and easier for the team.
Support access control and governance: Help design and operate role-based access control, least-privilege access, and governance controls across our cloud, warehouse, and BI platforms.
Contribute to data pipelines: Build, operate, and troubleshoot pipelines and transformations that power reporting, analytics, finance workflows, and data products across the company.
Support our platform migration: Help move workloads from our legacy stack to the modern data platform, including validation, cutover, and decommissioning work.
Document how things work: Write clear runbooks, platform documentation, and operational guides so knowledge is easier to share and the team is less dependent on any one person.
Use and improve AI-assisted engineering: Work with our Claude Code-based tooling, including agents, skills, hooks, and MCP integrations, and help shape how the team uses AI to improve engineering workflows.