Data Engineer - Paris - CDI
Indexed description
At the heart of our mission:
- A simple and understandable user experience
- Putting technology at the service of tomorrow's insurance
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 :)
- 💸 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
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.
- 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.
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
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.
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.
- 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.
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