Data Architect (BigQuery / GCP)

WildBrain•Toronto, ON

3d•Hybrid

About The Position

WildBrain is building an enterprise data warehouse on Google BigQuery as the single source of truth for financial and operational reporting across the business. The warehouse sits at the centre of our digital transformation, alongside a global ERP rollout (Microsoft Dynamics 365 Business Central with Binary Stream), a modern data pipeline stack, and an AI enablement agenda. The data platform is the foundation that the rest of the program depends on. We are looking for a hands-on BigQuery / GCP Architect — someone who will both design the enterprise data warehouse and write the code to bring it to life. This is explicitly not a "manager who reviews other people’s code" role. You will be in the platform every day — designing models, writing SQL and Python, building pipelines, setting the engineering standards others will follow, and lifting the bar on the platform team.

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.

Nice To Haves

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.

Responsibilities

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).