Job Description

We're hiring an Intermediate Snowflake Engineer to build and operate production-grade data platforms on Snowflake. You'll design and implement ELT/CDC pipelines, configure data zones end-to-end, publish governed data products, and harden security, quality, and cost controls.

Your future duties and responsibilities

. Configure data zones (Landing/External Stage, Bronze, Silver, Gold, Quarantine, Vault/Restricted, Sandbox) with clear naming, retention, and access patterns; implement Streams/Tasks/dbt jobs per zone.

. Publish governed data products: define domain-oriented tables/views with owners, contracts (schemas, SLAs/SLIs), documentation, and versioning/deprecation rules with architect

. Data quality & controls: implement validation at zone boundaries (schema/type, referential integrity, duplicate detection, PII tagging), route failures to Quarantine, and expose DQ metrics (freshness, completeness, latency) to stakeholders.

. Pipelines & ingestion: build batch and near-real-time ELT to Snowflake using tools like dbt, Openflow, Airflow/ADF; automate with Snowpipe/Snowpipe Streaming, Streams & Tasks.

. Modeling & serving: design dimensional and subject-area models; publish marts/semantic layers for BI/AI (Power BI/Fabric, Tableau, Looker) with stable contracts.

. Security & governance: implement RBAC, dynamic masking, row-access policies, object tagging/classification (PII/PCI), SSO (SAML/OIDC), SCIM; keep logs/keys in-geo and align to Canadian residency requirements.

. Performance & cost: right-size/auto-suspend warehouses, tune SQL and micro-partitioning, set Resource Monitors and budgets; analyze ACCOUNT_USAGE/INFORMATION_SCHEMA.

. Observability & reliability: add freshness/liveness/completeness SLIs and alerts, create runbooks/lineage, manage incidents and post-mortems; implement CI/CD (Git) and automated tests (dbt tests/Great Expectations).

. Legacy migrations: support one-time loads and CDC cutovers (e.g., IBM DB2 / iSeries) with row-count/checksum validation and reconciliations.

. Collaboration & documentation: partner with analytics, platform, and data governance teams; write ADRs, data contracts, and clear user docs.

Required qualifications to be successful in this role

. 2-5 years in data engineering (incl. 1+ years with Snowflake in production).

. Strong SQL (analytic functions, windowing, CTEs) and practical performance tuning on Snowflake.

. Hands-on with dbt (models/macros/tests), ELT patterns, and at least one orchestrator (Airflow or Azure Data Factory or Apache Nifi).

. Experience with Snowflake features: Warehouses & resource monitors, Time Travel/Fail-safe, Streams & Tasks, Snowpipe, external stages, file formats, data sharing.

. Security & governance basics: RBAC, masking/row policies, secrets handling, audit/log usage.

. CI/CD with Git; scripting in Python or SQL/PS for automation.

. Solid grasp of data modeling and data quality (tests, SLAs for freshness/latency).





Nice to have



. CDC from DB2 (e.g., Qlik Replicate, Fivetran HVA, IBM CDC).

. Azure experience (Key Vault, Private Link, VNet, ADF, Microsoft Fabric/OneLake); or AWS equivalents (S3, Glue, MSK).

. Snowpark (Python), User-Defined Functions/Procedures, Tasks with Python.

. Iceberg / External Tables and lakehouse patterns; partitioning and file layout best practices.

. dbt artifacts in CI (Slim CI, state-based testing), Great Expectations, Monte Carlo/Observability tools.

. BI experience with Power BI and semantic models

. Data privacy/regulatory awareness (PIPEDA, SOC 2, PCI segments).



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