{"id":116835,"url":"https://alion.io/job/passage-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":26791,"name":"Passage","domain":"passage.ai","url":"https://alion.io/company/passage","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":58,"open_postings":10,"ghost_share":0.7,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":58000,"max_usd":104000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":117},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Apache Kafka","optional":false},{"name":"BigQuery","optional":false},{"name":"dbt","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Fivetran","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Google GKE","optional":false},{"name":"GraphQL","optional":false},{"name":"Metabase","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Slack","optional":false},{"name":"Django","optional":true},{"name":"Docker","optional":true},{"name":"ETL/ELT","optional":true},{"name":"GCP","optional":true},{"name":"Helm","optional":true},{"name":"Kubernetes","optional":true},{"name":"Looker","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-08-06T18:53:53Z","employer_posted_date":"2026-08-06","last_verified_at":"2026-10-17T02:40:20Z","board_verified":true,"closed_at":null,"days_open":71,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":70},"description":"About Passage\nPassage helps international students navigate their journey abroad - from choosing a program and getting admitted to financing their studies and helping with their visa.\nThe role\nYou'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.\nThis 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.\nWhat you'll do\nModel 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.\n\nOwn metrics people rely on. Executive KPIs, conversion funnels, cohort analytics, and marketing attribution across Google Ads, Meta Ads, and UTM/click-ID data.\n\nRun 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).\n\nServe 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.\n\nTurn 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.\n\nKeep quality and cost in check. dbt tests, per-model documentation, BigQuery partitioning/clustering, and bytes-scanned discipline.\n\nDocument 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.\n\nOur stack\nBigQuery · dbt · Airflow 3 · Debezium + Kafka Connect (GKE) · Airbyte · Fivetran · Hasura · Metabase · PostgreSQL (Django app) · Docker · GCP · AI-assisted development\nYou might be a great fit if you\nHave 4+ years building analytics or data platforms, with expert-level SQL.\n\nHave run dbt in production and have real dimensional-modeling instincts - you think in grain, and SCD Type 2 doesn't scare you.\n\nHave operated an orchestrator (Airflow or similar) and are comfortable in Python.\n\nEnjoy ambiguous business-logic modeling: reverse-engineering a production schema, interviewing stakeholders, and shipping a table that settles the debate.\n\nWrite documentation people actually use.\n\nCan own a platform solo: prioritize, communicate, and ship without a spec.\n\nNice to have\nCDC pipelines (Debezium, Airbyte) or Kafka Connect; Kubernetes/Helm exposure.\n\nBigQuery performance and cost tuning.\n\nHasura/GraphQL, reverse ETL, or embedding warehouse data into product surfaces.\n\nMetabase or Looker administration.\n\nExperience as an early or solo data hire at a startup.\n\nFluency with AI-assisted development workflows.\n\nWhat success looks like in the first six months\nYou run the platform day to day - pipelines, tests, and monitoring - and stakeholders don't feel a handoff.\n\nYou've shipped new marts or metrics for at least two teams, from stakeholder conversation to documented, tested tables.\n\nData quality and freshness are visibly better: fewer surprises, faster answers.\nReady to join us?\nWe are building a company designed to expand access to life-changing opportunities around the world.\nIf you are excited about building systems, solving complex problems, and shaping how a company makes decisions, we would love to meet you.\nNote: Artificial intelligence may be used in the screening or assessment of applicants.\nIf your experience does not match every requirement but you believe you can thrive in this role, we encourage you to apply.\nCompensation\nC$100K to C$150K + Offers Equity","description_format":"text","description_chars":4330,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Consumer Loans & Pawnshops"],"lifecycle":[{"event":"open","at":"2026-08-06T18:53:53Z"}],"visa":[{"country":"CA","licensed_sponsor":true,"evidence":"Positions approved through LMIA in 12 months: 1","filings_12m":1,"filings_prev_12m":2,"green_card_filings_12m":null,"median_offered_wage_usd":null,"route":"Global Talent Stream","cap_exempt":false,"checked_at":"2026-10-03T21:10:52+00:00","sources":["ESDC: employers issued a positive LMIA"],"filings_for_role_12m":0}],"liveness":{"score":7,"band":"cold","label":"Long shot","p_open":1,"p_active":0.257,"p_room":0.28,"age_days":70,"expected_fill_days":31,"reasons":["conf:0","stale_co","win:tail","crowd:"],"computed_at":"2026-10-16T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/passage-senior-analytics-engineer","json_url":"https://alion.io/job/passage-senior-analytics-engineer.json","meta":{"generated_at":"2026-10-17T03:58:57Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":5201,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":26791},"rest":"https://alion.io/mcp/rest/get_company?id=26791"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fpassage-senior-analytics-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fpassage-senior-analytics-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fpassage-senior-analytics-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/passage-senior-analytics-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fpassage-senior-analytics-engineer"}]}