Skip to content

Open nowPosted 88 days ago

Founding Analytics Engineer

Zefir10 open roles

Pay
€85,300 – €93,800 a year
Where
Paris
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowFounding Analytics EngineerZefir · Paris
  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Zefir's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Zefir postings stay open a median of 57 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: posted 88 days ago

Zefir median: 57 days open

The posting

WHO WE ARE

Zefir 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.

Backed 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.

An 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.

WHY THIS ROLE EXISTS

This is the first dedicated data hire in years. The foundations run, the steering is up to you.

While 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.

Today 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.

You will be the single accountable owner of that layer. Not a support function, not a ticketing desk, not a BI factory.

WHAT YOU WILL OWN

Canonical 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.

Self-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.

Analytics 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.

Platform 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.

Data 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.

WHAT SUCCESS LOOKS LIKE AFTER 12 MONTHS

- One documented event taxonomy, actually used by Engineering, Growth and CRM.

- One 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.

- Published freshness and failure SLAs, an explicit ingestion topology, and no production path depending on BI tables.

- Ops, Growth, Finance and AMs build most of their recurring dashboards themselves, and AI agents query the data layer safely through curated MCPs.

- Growth attribution is trustworthy enough that annual acquisition spend decisions are defensible end to end.

WHAT WE ARE LOOKING FOR

- 7+ 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.

- Hands-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).

- You have shipped event tracking and instrumentation in production, end to end: taxonomy, client and server-side events, attribution, GDPR-compliant opt-out, propagation downstream.

- Comfortable with ingestion patterns (Fivetran, Airbyte, CDC), reverse-ETL (Hightouch, Census, Segment), and access governance (IAM, row- and column-level security, PII tagging).

- You have built and owned a semantic or metrics layer, and you can arbitrate metric definitions with Finance, Ops and Growth without flinching.

- You treat AI agents as first-class data consumers: exposing data through MCPs, semantic APIs or text-to-SQL, with proper guardrails.

- Strong ownership: you write the standards, defend them, and fix what is broken without waiting for permission.

- A clear communicator who turns "ping the data person" rituals into self-serve handoffs.

- Fluent in English and French.

THE HONEST TRADE-OFF

There 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.

It suits a doer’s mindset, including someone who has already led and wants to go back to building.

HIRING PROCESS

1. Screening with David, Talent (30 min)

2. Deep dive with Gabriel, Engineering Lead: your past experience and what you want next (45 min)

3. Technical interview with Diane, your future manager: data platform, modeling and tracking (1h)

4. Cultural interview with Louis, co-founder, plus an informal exchange with a function lead (1h)

5. Reference calls, then offer 🎉

BENEFITS

THE FOLLOWING IS FOR PERMANENT EMPLOYEES ONLY. FOR OTHER CONTRACTS (INTERNS, APPRENTICES, FIXED-TERM..), PLEASE, CHECK WITH YOUR RECRUITER.

- Competitive salary: You can run your own simulation with our salary calculator https://www.zefir.fr/zefir-salary-calculator.

- BSPCE (Stock Options): Available for everyone, with monthly vesting after year one, over a 4-year period.

- Healthcare plan: Full coverage with Alan for team members, their partners, and children.

- Office in Le Peletier, Paris (9th arrondissement): With flexible remote work options.

- Swile meal card: €11 per worked day.

- Swile mobility card: €45/month to support sustainable transportation (metro, carpooling, biking…).

- Team events: Monthly Mixers to connect and share good times, and quarterly All Hands to celebrate wins across the company.

OUR OPERATING PRINCIPLES

🏔️ Steep Mountains Are Steep: Setting ambitious goals and working hard to achieve them.

🌊 Ride Reality: Actively seeking challenges and thriving by adapting flexibly to changes.

🏀 Play for the Front of the Jersey: Prioritizing team success over individual recognition.

APPLICATION & PROCESS

We welcome applications from anyone, regardless of background, gender, sexual orientation, religion, age, or experience. Our team values authenticity and diverse perspectives.

For all roles, our interview process emphasizes hands-on exercises, case studies, or discussions about specific examples of your previous work. We ensure objectives and expectations are clearly communicated at every step.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Zefir's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.
  3. We apply on Zefir's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.
  4. Every reply, sorted

    Zefir's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.
  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.