Remote Senior Data Engineer: Data Platform & AI Readiness

Dandy; Canada; Remote; CAD 120,000 - 170,000; Full time

Benefits offered by this job

Healthcare

Dental

Mental health support

Retirement savings options

Generous paid time off

Job summary

Dandy is hiring a hands-on Senior Data Engineer to join its data infrastructure team in Canada. You’ll design, build, and scale ingestion pipelines and the warehouse feeding Looker and Hex, supporting multiple teams with trusted self-serve data products.

You’ll help lay the foundation for an AI/agent-ready data platform. We value 5+ years in data engineering, production pipeline experience, expert SQL, and Python for tooling.

Qualifications

• 5+ years of experience in data engineering or SQL-heavy analytics roles.
• Production experience building data ingestion pipelines and transformations (dbt or equivalent).
• Expert-level SQL with Python or similar for tooling/automation.
• Hands-on with Looker, Hex, dbt or equivalent BI tools.
• Able to collaborate across Finance, GTM, Manufacturing, and ML to deliver data products.
• Experience establishing data engineering processes in ambiguous environments.

Responsibilities

• Design, build, and operate ingestion pipelines and connectors landing data into the warehouse.
• Own core platform components (dbt models, semantic layer, data quality/observability).
• Partner with stakeholders to translate business needs into governed, self-serve data products.
• Support AI/agent-ready data platform with governed access and safety guardrails.

Skills

SQL

Python

dbt

Looker

Hex

Data pipelines

Cross-functional collaboration

Tools

BigQuery

Looker

Hex

Job description

Dandy is hiring a hands-on Senior Data Engineer to join its data infrastructure team in Canada. You’ll design, build, and scale ingestion pipelines and the warehouse feeding Looker and Hex, supporting multiple teams with trusted self-serve data products.

You’ll help lay the foundation for an AI/agent-ready data platform. We value 5+ years in data engineering, production pipeline experience, expert SQL, and Python for tooling.