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Data Architect (BigQuery / GCP)

External
Wildbrain logoWildbrain · Toronto, Canada
Full-timeOn-site1w ago
AirflowBigQueryCI/CDClassificationClusteringdbt
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Requirements

  • Strong track record of building data platforms, with deep BigQuery and GCP in a hands-on capacity.
  • Expert-level SQL - you can write, optimize, debug, and explain anything in BigQuery, including window functions, complex joins, and cost-sensitive query patterns.
  • Strong Python for data engineering - pipelines, orchestration, testing, packaging.
  • Production experience with the modern GCP data stack - Cloud Composer (Airflow), Dataflow, Pub/Sub, Cloud Storage, Cloud Functions.
  • Production experience with dbt or Dataform for modelling and transformation.
  • Strong dimensional modelling background; data vault experience is a plus.
  • Experience designing warehouses for financial reporting - GL, sub-ledger, intercompany, consolidation.
  • Strong CI/CD discipline - Git, automated testing, deployment pipelines.
  • Ability to operate at architect altitude while still shipping code every week.
  • Experience integrating Microsoft Dynamics 365 Business Central data into BigQuery.
  • Streaming pipeline experience (Pub/Sub, Dataflow streaming).
  • Looker, Power BI, or other semantic-layer experience.
  • Exposure to ML / GenAI on GCP - Vertex AI, BigQuery ML, embeddings
  • Experience standing up a brand new enterprise data platform from greenfield.

Benefits

Working at WildBrain is more than a job - it's the opportunity to join forces with extraordinary, insightful and imaginative people who will recognize your talents and encourage your professional growth and development in a work environment that promotes creativity and individuality.Our CommitmentAbout WildBrain

Additional Information

Architect and build the enterprise data warehouse on BigQuery to support financial, operational, and management reporting. Design the data model - raw, staging, curated, and semantic layers - and the standards that govern how new data lands and is transformed. Hands-on build of pipelines from source systems (ERP, billing, HR, operational sources) into BigQuery. Select and operate the right GCP services across the stack -Dataflow, Pub/Sub, Cloud Functions, Cloud Storage, Dataform / dbt. Establish engineering standards - version control, CI/CD, testing, documentation, monitoring, lineage - and enforce them through code review. Own data quality, freshness, observability, and cost optimization on BigQuery (partitioning, clustering, slot management). Partner with finance and business stakeholders to translate reporting needs into durable models, not one-off extracts. Lead by example - code reviews, architectural decision records, pairing, and lifting the team's bar without becoming a bottleneck. Establish data governance practices - IAM, access controls, PII handling, data classification, and audit. Provide thought leadership on the path from a reporting warehouse to an AI-ready data foundation (feature stores, BigQuery ML, Vertex AI integration).

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