{"id":790611,"url":"https://alion.io/job/zefir-founding-analytics-engineer","title":"Founding Analytics Engineer","company":{"id":688165,"name":"Zefir","domain":"zefir.fr","url":"https://alion.io/company/zefir-3","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":70,"open_postings":10,"ghost_share":0.5,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-01T06:10:25Z"}},"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":["Paris, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":85300,"max":93800,"currency":"EUR","period":"year","gross":null,"usd_annual":105292},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fivetran","optional":false},{"name":"GDPR","optional":false},{"name":"Google BigQuery","optional":false},{"name":"IAM","optional":false},{"name":"Prefect","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-08-07T17:27:14Z","employer_posted_date":"2026-08-07","last_verified_at":"2026-11-01T18:05:41Z","board_verified":true,"closed_at":null,"days_open":86,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":85},"description":"Who We Are\nZefir is building an AI autopilot for home sales in Europe, starting in France: an AI agent runs the entire sale and purchase journey end-to-end, orchestrating local brokers, portals, buyers, and documents.\nBacked by €60 million from top-tier investors Sequoia Capital and Kima Ventures, we're committed to accelerating life changes for millions of current and future European homeowners.\nAn AI agent that runs a property transaction end to end only works if the data underneath it is available, reliable and governed. That is the job.\nWhy this role exists\nThis is the first dedicated data hire in years. The foundations run, the steering is up to you.\nWhile BigQuery already houses most of our data, we still lack key Growth data and a cohesive data governance framework. We need unified definitions, a canonical schema, and a robust semantic layer, enabling Growth, Finance, Ops and Product to self-serve insights efficiently and reliably.\nToday the stack holds because individuals across Ops, Growth, Finance and Engineering compensate locally. They learned the quirks and built workarounds. It works, but it is fragile: KPIs drift between tools, tracking breaks silently, costs escalate, and nobody owns the translation between raw engineering data and decision-ready truth.\nYou will be the single accountable owner of that layer. Not a support function, not a ticketing desk, not a BI factory.\nWhat you will own\nCanonical models and metric definitions. A documented semantic layer with canonical entities (Buyer, Seller, Asset, Agent) and Bronze / Silver / Gold layers. Clear contracts between what Engineering exposes and what each function consumes, so that KPI debates are aligned on the same metric.\nSelf-serve enablement. The submerged part of the iceberg: clean models, consistent BI primitives, row- and column-level security, so Ops, Growth, Finance and Account Managers build their own dashboards without compromising on accuracy.\nAnalytics and tracking governance. The global event taxonomy and tracking roadmap, a hybrid client-side and server-side event strategy, consistent sync across CRMs and marketing platforms, and GDPR consent flows by design, so acquisition spend runs on attribution we can trust.\nPlatform reliability, safety and cost. Standards set once rather than team by team: tested and versioned transformations, monitoring of freshness, failures and usage, sane ingestion patterns (read replicas, CDC, batch), and no production code path depending on BI tables.\nData and AI driving decisions. Our internal AI tooling already queries the data warehouse for analyses. What’s missing is the core foundation: standardized metric definitions, reusable logic, and pre-computed data models.\nWhat success looks like after 12 months\nOne documented event taxonomy, actually used by Engineering, Growth and CRM.\n\nOne semantic layer where every shared KPI has a single definition, a single owner and a version history. New joiners understand the data model in days, not months.\n\nPublished freshness and failure SLAs, an explicit ingestion topology, and no production path depending on BI tables.\n\nOps, Growth, Finance and AMs build most of their recurring dashboards themselves, and AI agents query the data layer safely through curated MCPs.\n\nGrowth attribution is trustworthy enough that annual acquisition spend decisions are defensible end to end.\n\nWhat we are looking for\n7+ years as a Data, Analytics or Platform Engineer, ideally including a stint at a fast-moving consumer or marketplace company. Staff or Lead exposure expected.\n\nHands-on with the modern data stack: BigQuery (or Snowflake, Redshift), dbt or equivalent, advanced SQL and data modeling, Python for pipelines, orchestration (Airflow, Dagster, Prefect).\n\nYou have shipped event tracking and instrumentation in production, end to end: taxonomy, client and server-side events, attribution, GDPR-compliant opt-out, propagation downstream.\n\nComfortable with ingestion patterns (Fivetran, Airbyte, CDC), reverse-ETL (Hightouch, Census, Segment), and access governance (IAM, row- and column-level security, PII tagging).\n\nYou have built and owned a semantic or metrics layer, and you can arbitrate metric definitions with Finance, Ops and Growth without flinching.\n\nYou treat AI agents as first-class data consumers: exposing data through MCPs, semantic APIs or text-to-SQL, with proper guardrails.\n\nStrong ownership: you write the standards, defend them, and fix what is broken without waiting for permission.\n\nA clear communicator who turns \"ping the data person\" rituals into self-serve handoffs.\n\nFluent in English and French.\n\nThe honest trade-off\nThere is no data team to manage, and none planned in the short term. You get real autonomy and a direct line to the founders and function leads, in exchange for building alone before maybe building a team. At a comparable proptech you would join an existing team and an existing roadmap. Here, what a metric means at Zefir is not decided yet, and you are the one who decides it.\nIt suits a doer’s mindset, including someone who has already led and wants to go back to building.\nHiring process\nScreening with David, Talent (30 min)\n\nDeep dive with Gabriel, Engineering Lead: your past experience and what you want next (45 min)\n\nTechnical interview with Diane, your future manager: data platform, modeling and tracking (1h)\n\nCultural interview with Louis, co-founder, plus an informal exchange with a function lead (1h)\n\nReference calls, then offer\n\nBenefits\nThe following is for permanent employees only. For other contracts (interns, apprentices, fixed-term..), please, check with your recruiter. \nCompetitive salary: You can run your own simulation with our salary calculator.\n\nBSPCE (Stock Options): Available for everyone, with monthly vesting after year one, over a 4-year period.\n\nHealthcare plan: Full coverage with Alan for team members, their partners, and children.\n\nOffice in Le Peletier, Paris (9th arrondissement): With flexible remote work options.\n\nSwile meal card: €11 per worked day.\n\nSwile mobility card: €45/month to support sustainable transportation (metro, carpooling, biking…).\n\nTeam events: Monthly Mixers to connect and share good times, and quarterly All Hands to celebrate wins across the company.\n\nOur Operating Principles\nSteep Mountains Are Steep: Setting ambitious goals and working hard to achieve them.\nRide Reality: Actively seeking challenges and thriving by adapting flexibly to changes.\nPlay for the Front of the Jersey: Prioritizing team success over individual recognition.\nApplication & Process\nWe welcome applications from anyone, regardless of background, gender, sexual orientation, religion, age, or experience. Our team values authenticity and diverse perspectives.\nFor all roles, our interview process emphasizes hands-on exercises, case studies, or discussions about specific examples of your previous work. 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