Data Engineer

Mission: Build and operate the data pipelines that land, transform, and model data on the

Snowflake platform reliably and efficiently.

Key responsibilities:

- Develop and maintain ingestion pipelines from source systems into Snowflake, covering both batch and streaming (e.g., Snowpipe, Streams & Tasks, connectors).
- Build transformation and data-modelling logic using SQL, dbt, and/or Snowpark (Python/Java).
- Implement automated testing, data-quality checks, monitoring, and alerting across pipelines.
- Apply CI/CD and version control so pipeline changes are reviewed, tested, and deployed consistently.
- Optimize queries and warehouse usage for performance and cost (pruning, clustering, rightsizing).
- Document data lineage, transformations, and operational runbooks.

Qualifications:

- 3+ years in data engineering; solid SQL and Python; hands-on experience with ELT/ETL tooling, dbt, and orchestration (e.g., Airflow, dbt Cloud)
- Git-based version control and CI/CD familiarity; exposure to streaming ingestion a plus.
- SnowPro Core certification preferred.

Key skills: SQL, Python, dbt, pipeline orchestration, data quality, performance tuning, Git/CI-CD.

📌 Snowflake Data Engineer (Greater Toronto Area)
🏢 Hydro One
📍 Greater Toronto Area