Role snapshot

- Title: Data Engineer – Snowflake
- Location: Toronto, ON (hybrid, 2–3 days on-site)
- Engagement: Full-time, placed with an Augmented enterprise client
- Level: Intermediate to Senior (4+ years in data engineering)
- Reports to: Data Platform / Engineering Lead

About the roleAugmented is hiring a Data Engineer to build and scale a Snowflake data platform for one of our large enterprise clients in a regulated industry. You will design reliable ingestion and transformation pipelines, model data for analytics and AI use cases, and help move legacy warehouse workloads to the cloud. You will join a small, senior delivery team that works directly with client stakeholders. The work spans greenfield builds and migrations, with a strong focus on data quality, governance and cost.

Key responsibilities

- Design and build Snowflake data pipelines using layered (raw/staging/curated) architecture
- Ingest batch and near-real-time data from databases, APIs, files and event streams using Snowpipe, Snowpipe Streaming, Fivetran or CDC tools
- Build ELT transformations in SQL and dbt; use Streams, Tasks and Dynamic Tables for incremental processing
- Model curated data sets (dimensional, Data Vault or wide tables) for BI, analytics and ML teams
- Tune warehouse sizing, clustering and query performance; monitor and control credit spend
- Implement data quality tests, lineage and observability; own pipeline SLAs and incident response
- Apply governance and security: RBAC, masking and row access policies, tagging and PII handling
- Migrate legacy warehouse and ETL workloads (e.g. Teradata, Oracle, SQL Server, Informatica) to Snowflake
- Build CI/CD for data code and infrastructure-as-code for Snowflake objects
- Partner with client architects, analysts and data scientists; document designs and decisions

Required qualifications
- 4+ years in data engineering, with 2+ years building on Snowflake in production
- Advanced SQL and strong Python




- Hands-on dbt experience (models, tests, macros, documentation)
- Experience with at least one major cloud: AWS, Azure or GCP (storage, IAM, networking basics)
- Orchestration with Airflow, Dagster, dbt Cloud or Azure Data Factory
- Solid grasp of data modelling, Snowflake performance tuning and cost management
- Git-based workflows and CI/CD (GitHub Actions, Azure DevOps or GitLab)
- Clear communicator, comfortable working directly with enterprise client teams
- Legally entitled to work in Canada

Nice to have
- SnowPro Core or SnowPro Advanced: Data Engineer certification
- Snowpark (Python), Snowflake Cortex or other in-platform ML/AI features
- Terraform or schemachange for Snowflake object management
- Experience in Life Sciences (GxP, clinical or commercial data) or Financial Services (risk, payments, regulatory reporting)
- Data sharing, Snowflake Marketplace or data product design
- Consulting or client-facing delivery background

Tech stack
- Platform: Snowflake (Streams, Tasks, Agile Tables, Snowpark)
- Languages: SQL, Python
- Cloud: AWS (S3) or Azure (ADLS Gen2)
- Ingestion: Snowpipe / Snowpipe Streaming, Fivetran, Kafka, CDC tools
- Transformation: dbt (Core or Cloud)
- Orchestration: Airflow, Dagster, dbt Cloud, Azure Data Factory
- DevOps: Git, CI/CD pipelines, Terraform
- Consumption: Power BI, Tableau, Sigma

Why AugmentedAugmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.
- Work on high-impact data platforms for enterprise clients
- Small, senior teams with direct access to client decision-makers
- Exposure to AI-native delivery practices and modern tooling
- Compensation: [salary range to confirm] plus benefits

How to applyApply through this posting with your resume and a short note on a Snowflake pipeline you built (scale, stack, your role). Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.

📌 Data Engineer Snowflake (Toronto)
🏢 Augmented
📍 Toronto