SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: CAD 100,000 - 150,000 / annual
Passage helps international students navigate their journey abroad—from program selection and admissions through financing and visa support. You'll own the company's data platform end-to-end, taking full responsibility for a mature, documented warehouse that already powers executive KPIs, marketing attribution, funnel analytics, and internal operations tools.
You'll model the business in dbt on BigQuery, managing a ~100-model project built on Kimball dimensional modeling principles (SCD Type 2 dimensions, fact tables with explicit grain, aggregate tables). Recent work includes applicant milestone tracking, loan-process stage modeling, and ad-click-level attribution across Google Ads, Meta Ads, and UTM/click-ID data.
You'll run Airflow 3 orchestration with Slack alerting, data-quality tests, and freshness monitoring. Data ingestion uses CDC from production Postgres via Debezium + Kafka Connect on GKE, supplemented by Airbyte and Fivetran. A dedicated dbt serving layer exposed through Hasura GraphQL powers internal ops tools; Metabase serves dashboards and self-serve queries.
Much of the work involves translating messy operational reality into trustworthy tables: screening outcomes, payment and fee states, deferral lineage, guarantor chains. You'll dig into source systems, interview stakeholders, and encode business logic. You'll maintain quality and cost discipline through dbt tests, per-model documentation, BigQuery partitioning/clustering, and bytes-scanned discipline. Documentation is critical—every model is documented and synced to a companion repo so teammates and AI agents can query the warehouse correctly.
You should have 4+ years building analytics or data platforms with expert SQL, production dbt experience with dimensional-modeling instincts, and comfort operating orchestrators like Airflow in Python. You enjoy ambiguous business-logic modeling and can own a platform solo: prioritize, communicate, and ship without a spec. Nice-to-haves include CDC pipelines, Kubernetes/Helm exposure, BigQuery tuning, Hasura/GraphQL, reverse ETL, Metabase/Looker administration, early-stage startup data experience, and AI-assisted development fluency.
