Orus is a European insurtech company that is growing fast and full of ambition. The idea was born from a simple observation: professional insurance is too complex and not very effective. Professionals don't know what coverage they need, how and when it applies, and often end up unprotected or poorly covered. Orus is therefore the insurance professionals have been waiting for: simple, fast, transparent, and above all human.

At the heart of our mission:

A simple and understandable user experience
Putting technology at the service of tomorrow's insurance

To achieve this, Côme, Tom and Samuel, co-founders of Orus, raised 25 million euros in a Series B round. This was also an opportunity to be backed by top funds and private investors, including the CEOs of Pennylane, Hiscox Europe, and Leocare. 💙

Why join us?

You'll grow within a fast-growing startup
A senior team with backgrounds at top startups (PayFit, Qonto, Alan, etc.)
In a supportive environment, which is particularly important at Orus
And we're already the French favorite insurtech, with 4.9 stars on TrustPilot :)

What we offer

💸 BSPCE: every Orus employee is also a shareholder
💻 Laptop of your choice (Apple, Linux, or Windows)
☕️ Spacious offices in Paris's 9th arrondissement
👩‍💻 Flexible hybrid-work policy
✨ Health insurance with Sidecare
🍏 €9 Swile meal vouchers
🏝 25 days of paid vacation plus 10 RTT days

The role

The data we collect and transform supports decision-making across Orus, from insurance product design and underwriting to regulatory reporting and customer engagement. As the company grows, we need a data platform that remains reliable, well documented, and easy to use.

You will join as Orus's second Data Engineer and work closely with Davi, our first Data Engineer, as a peer. Together, you will increase the Data Engineering team's capacity, reduce its dependence on a single engineer, and improve the quality of its architecture decisions. You will contribute across the platform and progressively take ownership of significant areas as your understanding of the systems and business grows.

Your responsibilities

Build and maintain a data quality and reliability framework using dbt tests, monitoring, clear ownership, and a defined severity model.
Improve the data development environment, including CI/CD for dbt, review standards, documentation, and data contracts.
Promote data culture and self-service by documenting tables, helping teams use data autonomously, and improving data marts for business needs.
Work closely with teams across Orus:
- Partner with Analytics to build data marts that help the team create value from data.
- Support Growth in using customer data for communication automation.
- Partner early with Insurance and Engineering so data requirements, reporting models, and quality checks are ready before each product launch.
Proactively map and integrate internal and external data sources into the data warehouse, moving from reactive ingestion to a prioritized source roadmap.
Maintain and evolve event-driven data pipelines, mainly written in TypeScript and connected directly to the application backend.
Build and maintain a governed semantic layer that enables accurate AI-agent answers and faster access to business information across Orus.

What success looks like

During your first 6–12 months, you will help the team:

Increase delivery capacity and reduce dependence on a single Data Engineer.
Put an operational data quality framework in place, with automated tests, monitoring, severity levels, ownership, and a clear response process.
Improve the dbt development workflow with reliable CI/CD, documentation, review standards, and appropriate data contracts.
Make event-driven pipelines more observable and maintainable while reducing technical debt.
Anticipate upcoming source-integration needs instead of responding only when requests arrive.
Enable business teams to find, understand, and use trusted data with less support from Data.
Extend the semantic layer so AI agents can answer accurately across more business domains.
Contribute actively to architecture discussions and take ownership of meaningful areas of the platform.

Technical context

Orus's product uses event sourcing: every change in the system is captured as an event. Our data platform ingests these events in real time and also integrates batch data from external sources.

Data stack

dbt Cloud — data transformation, documentation, and testing
BigQuery — data warehouse
MongoDB — main application database
TypeScript — event-driven pipelines connected to the application backend
Fivetran — external-source ingestion
Hightouch — reverse ETL
Metabase — data exploration and quick access
Looker Studio — main analytics tool for the Analytics team
Google Cloud, Terraform, Kubernetes, and Argo CD — infrastructure and production operations

External data sources

Our sources include HubSpot, Aircall, Teamtailor, Webflow, lead-generation partners, Meta Ads, Google Ads, and product-behavior data currently being migrated from Segment to PostHog.

Day-to-day work

Your day-to-day responsibilities will include:

Shaping and prioritizing data requests with stakeholders.
Assessing data impacts with Engineering when the application or back office changes.
Communicating project progress, risks, and decisions clearly.
Monitoring data quality and resolving production issues.
Developing and improving SQL models.
Pairing with Davi and contributing to technical and architecture decisions.

Profile sought

We are looking for a hands-on Data Engineer at mid-to-senior level. Candidates will usually have at least three years of relevant experience, but demonstrated scope, judgment, and autonomy matter more than tenure or a specific degree.

Must have

Strong SQL proficiency.
Hands-on experience with dbt.
Strong understanding of at least one modern cloud data warehouse, such as BigQuery, Snowflake, Redshift, or ClickHouse.
Ability to reason about data models and architecture tradeoffs.
Willingness and ability to learn TypeScript.
Strong interest in collaborating with other teams and understanding the business.
Ability to connect technical choices to business goals.
Autonomy, initiative, clear communication, and a willingness to seek feedback.
Experience working in a startup or scaleup data team, ideally in SaaS, fintech, insurtech, or another data-intensive product environment.
Residence in Île-de-France and availability to work regularly from our Paris office. Full remote is not available for this role.

Nice to have

BigQuery and Google Cloud experience.
Experience with event-driven architectures.
TypeScript proficiency.
Experience with MongoDB and/or PostgreSQL.
Python proficiency.
Experience with Terraform, Kubernetes, or Argo CD.
Production experience with agentic data systems or semantic layers.

Career development

The role offers a path toward Senior and Staff-level individual-contributor scope, with increasing technical leadership and ownership of the data platform without requiring a move into people management.