Europe Arbeitnow ·
full-timeFounding Analytics Engineer
Zefir · Paris
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 over $55 million from top-tier investors like Sequoia Capital, 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 dec
| Role | Founding Analytics Engineer |
|---|---|
| Company | Zefir |
| Location | Paris |
| Compensation | Not disclosed |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4More at Zefir
Other jobs at Zefir
- Account Manager Junior · Paris
- Acquisition Lead, Performance Marketing · Paris
- Account Manager · Paris
- Business Development Representative (BDR) · Paris
- Sales Graduate Program (SDR - AEC) · Paris
Internships at Zefir
- Founder Associate (internship) · Paris
Explore Related Placements
// similar opportunities
You might also like
Analytics Engineer
Qonto
Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented ...
Senior Analytics Engineer
Dashlane
About Dashlane Dashlane’s mission is to deliver the credential security every business and employee needs to thrive. Millions of consumers, and over 25,000 bran...
Analytics Engineer
Ledger
We’re a team of experts pushing the limits of what’s possible, united by our common goal to unlock true freedom through digital ownership, making technology acc...
Analytics Engineer
Multiverse
Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming to...
Senior Analytics Engineer
Mercury
In 1989, Tim Berners-Lee wrote a proposal for CERN. CERN lost knowledge when people left, because its information was in many systems that did not connect. His ...
BI Analytics Engineer
Netskope
Join the Future of Security at Netskope Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate...