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 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 role

Augmented 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)

Explicit 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, Dynamic 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 Augmented

Augmented 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 Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.

📌 Data Engineer Snowflake (Toronto)
🏢 Augmented
📍 Toronto