Posted 3 months ago
Senior Analytics Engineer
@ Passage
Toronto, Ontario
Overview
Passage is hiring a Senior Analytics Engineer to own its data platform end to end. The role runs a dbt project on BigQuery, builds dimensional models and metrics for leadership, marketing and operations, and maintains Airflow pipelines and quality checks. The posting states a salary of C$100K to C$150K plus equity, and asks for 4+ years of analytics or data platform experience.
Responsibilities:
- Own and extend a ~100-model dbt project on BigQuery
- Build dimensional models, metrics and marketing attribution for leadership and teams
- Operate Airflow pipelines with tests, freshness monitoring and backfills
- Model business logic from operational source systems
Requirements summary:
- 4+ years building analytics or data platforms
- Expert-level SQL
- Production dbt experience and dimensional modeling skills
- Experience operating Airflow or a similar orchestrator
- Comfortable in Python
- Ability to own a platform solo
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-08-06
- First seen by our source
- 2026-10-08
- Source record updated
- 2026-10-09
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Data & analytics |
| Experience | 4+ years |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Perks mentioned | Stock or equity |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Passage
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
Our mission is to provide access to life-changing opportunities.
Full company description
Everyone should have equal access to opportunities. Passage matches top international talent with labor shortages in Canada and helps fund their journey. By 2030, our goal is to remove the financial barriers for study abroad and immigration.
- LinkedIn followers
- 9,754
- People associated on LinkedIn
- 71
- Reported office locations
- Toronto, Ontario, CA
- Business categories
- Human Resources
- Education
- Legal Tech
- EdTech
- Information Services
- Recruiting
- FinTech
- Financial Services
- Artificial Intelligence (AI)
- Other recorded names
- Passage
- Profile identifies a recruitment agency
- No
- Reported total investment
- 30,311,067
Currency and observation date were not supplied; this is not a current valuation or a funding round.
Everyone should have equal access to opportunities. Passage matches top international talent with labor shortages in Canada and helps fund their journey. By 2030, our goal is to remove the financial barriers for study abroad and immigration.
| Field | Value |
|---|---|
| Industry | Information Services |
| Company size | 11-50 employees |
| Headquarters | Toronto, Ontario |
| Organization type | Privately Held |
| Year founded | 2023 |
| Open jobs on Jobsy | 5 |
| View page |
About Passage
Passage helps international students navigate their journey abroad — from choosing a program and getting admitted to financing their studies and helping with their visa.
The role
You'll own Passage's data platform end to end. Not a greenfield project and not a legacy mess: a working, documented warehouse that the company already runs on — executive KPIs, marketing attribution, funnel analytics, and internal ops tools are all powered by it today. Your job is to take ownership, keep it trustworthy, and extend it as the business grows.
This is a high-leverage, high-trust seat. The models you build define how the company measures itself, and your stakeholders are leadership, marketing, and operations — not a ticket queue.
What you'll do
Model the business in dbt on BigQuery. Own a ~100-model project (staging → intermediate → marts) built on Kimball dimensional modeling: SCD Type 2 dimensions, fact tables with explicit grain, and aggregate tables for reporting. Recent work includes applicant milestone tracking, loan-process stage modeling, and ad-click-level attribution.
Own metrics people rely on. Executive KPIs, conversion funnels, cohort analytics, and marketing attribution across Google Ads, Meta Ads, and UTM/click-ID data.
Run the pipelines. Airflow 3 orchestration with Slack alerting, data-quality tests, freshness monitoring, and backfills. Ingestion is CDC from our production Postgres via Debezium + Kafka Connect on GKE (with Airbyte and Fivetran alongside).
Serve the data. A dedicated dbt serving layer exposed through Hasura GraphQL powers internal ops tools in the product itself; Metabase serves dashboards and self-serve queries.
Turn messy operational reality into tables people trust. Much of the work is business-logic modeling: screening outcomes, payment and fee states, deferral lineage, guarantor chains. You'll dig into the source system, talk to the people who run the process, and encode the truth.
Keep quality and cost in check. dbt tests, per-model documentation, BigQuery partitioning/clustering, and bytes-scanned discipline.
Document for humans and AI. Every model is documented, and the docs auto-sync to a companion repo built so both teammates and AI agents can query the warehouse correctly. We work AI-assisted, with coding standards written into the repos.
Our stack
BigQuery · dbt · Airflow 3 · Debezium + Kafka Connect (GKE) · Airbyte · Fivetran · Hasura · Metabase · PostgreSQL (Django app) · Docker · GCP · AI-assisted development
You might be a great fit if you
Have 4+ years building analytics or data platforms, with expert-level SQL.
Have run dbt in production and have real dimensional-modeling instincts — you think in grain, and SCD Type 2 doesn't scare you.
Have operated an orchestrator (Airflow or similar) and are comfortable in Python.
Enjoy ambiguous business-logic modeling: reverse-engineering a production schema, interviewing stakeholders, and shipping a table that settles the debate.
Write documentation people actually use.
Can own a platform solo: prioritize, communicate, and ship without a spec.
Nice to have
CDC pipelines (Debezium, Airbyte) or Kafka Connect; Kubernetes/Helm exposure.
BigQuery performance and cost tuning.
Hasura/GraphQL, reverse ETL, or embedding warehouse data into product surfaces.
Metabase or Looker administration.
Experience as an early or solo data hire at a startup.
Fluency with AI-assisted development workflows.
What success looks like in the first six months
You run the platform day to day — pipelines, tests, and monitoring — and stakeholders don't feel a handoff.
You've shipped new marts or metrics for at least two teams, from stakeholder conversation to documented, tested tables.
Data quality and freshness are visibly better: fewer surprises, faster answers.
Ready to join us?We are building a company designed to expand access to life-changing opportunities around the world.
If you are excited about building systems, solving complex problems, and shaping how a company makes decisions, we would love to meet you.
Note: Artificial intelligence may be used in the screening or assessment of applicants.
If your experience does not match every requirement but you believe you can thrive in this role, we encourage you to apply.
Compensation
C$100K to C$150K + Offers Equity
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