Intermediate/Senior Data Engineer

Il y a 4 mois

Paris, France Descartes Underwriting Temps plein

ABOUT DESCARTES UNDERWRITING

Descartes was born out of the conviction that the ever-increasing complexity of risks faced by corporations, governments and vulnerable communities calls for a renewed approach in insurance. Our team brings together industry veterans from the most renowned institutions (AXA, SCOR, Swiss Re, Marsh, Aon, ...) and scientists on top of their field to bring underwriting excellence. After 5 years of existence, Descartes has secured a leading position in parametric insurance for weather and climate-related risks utilizing machine learning, real-time monitoring from satellite imagery & IoT. After a successful Series B raise of $120M USD, we launched Descartes Insurance, a 'full stack' insurer licensed to underwrite risk by the French regulator ACPR. With a growing corporate client base (350+ and counting), our diverse team is headquartered in Paris and operates out of our 13 global offices in North America, Europe, Australia, Singapore, Hong Kong and Japan. Descartes is trusted by a panel of A-rated (re)insurers to carry out its activities.

ABOUT YOUR ROLE

Due to our consistent growth, we are expanding our Data, Software and DevOps team. We are seeking profiles dedicated to data engineering. At the core of the development of our scientific engine modeling climate phenomena, your main missions will be to create, improve and maintain the data pipelines used to train our model and infer the different scenarios to make a climate risk assessment. You will have to take initiative and assess the viability of proof-of-concept projects.

You will have to work with data scientists and software engineers to run and develop our models. You will be working alongside DevOps engineers to reliably put models in production and selected the compute/store instance needed to perform these tasks. Your secondary mission will be to automate the flow of information between the tech and business to monitor climate events.

🔔 KEY MISSIONS 🔔

Design, setup, and maintain:

  • Data pipelines and associated datalakes;
  • Connections to external and internal APIs;
  • Associated CI/CD and release pipelines;
  • Notification tools to inform the team of the status of the operations.

Propose and setup data storage, data processing and data visualizing tools including:

  • Assessing the pains and needs of the teams;
  • Benchmarking different solutions;
  • Assessing the security, price and reliability of data architecture;
  • Following the development the evolution of technologies on the topic;
  • Forecasting and tracking cloud spend.

Participate in:

  • Tech stack evolution;
  • Discussions with tech partners;
  • Training of other tech teams;
  • Support and debug of internal users.

TECH STACK 🖥️

  • Cloud provider: GCP
  • Code versioning tool: Git + Gitlab
  • OS: Windows
  • Container: Docker
  • Container orchestrator: Kubernetes
  • Code base: Python
  • Notification tool: Slack

DATA STACK

  • Types: images, time series, data frames, etc.
  • Pipeline orchestrator: Apache Airflow
  • Data stores: Cloud SQL, FireStore, BigQuery

In our project, data is collected by sensors (satellite, weather station, IoT). We don’t work with personal or sensitive data, in most cases the data is publicly available (earthquake magnitude, cyclone track, precipitation …).

ABOUT YOU

EXPERIENCE & QUALIFICATIONS 💻🖥️

[Hard skills]

  • Knowledge of the tech stack and demonstrated proficiency in production environments;
  • Minimum 3 years’ experience in Python object-oriented programming;
  • Experience converting Python code to efficient data engineering tools;
  • Production experience with Docker;
  • Production experience with a cloud provider (GCP, AWS or Azure);
  • CI/CD and release pipelines;
  • Good knowledge in English and fluency in French.

[Soft skills]

  • Excellent communication skills, in both formal and informal settings, and in English and French;
  • Contribute to a rigorous data engineering culture;
  • Propagate Data Engineer best practices to other tech teams;
  • Well versed in Agile;
  • Mentoring junior engineers.

[Nice-to-have]

  • Prior experience working in data science or scientific computing projects;
  • Working knowledge of DevOps;
  • Contribution to an open source project.

MINDSET 💥

  • Strong interest with climate issue (it’s not a hoax, many people suffer from it);
  • Being comfortable to work alongside corporate insurers (some still wear suits 👔);
  • You enjoy CI/CD automation (or at least appreciate the elegance of a well-crafted pipeline);
  • Strong team spirit and ability to work (you’ll have to review code and have your code reviewed);
  • Rigorous, creative and meticulous mind (we handle large insurance, we take our time);
  • Strong desire to learn (there’s no limitation to the tech used, we’re happy to test and learn new tools);
  • Eagerness to work in a multi-cultural environment (policies and teams are from all around the world 🗺️).

WHY JOIN DESCARTES UNDERWRITING?

  • Opportunity to work and learn with teams from the most prestigious schools and research labs in the world, allowing you to progress towards technical excellence;
  • Commitment from Descartes to its staff of continued learning and development (think annual seminars, training etc.) ;
  • Work in a collaborative & professional environment ;
  • Be part of an international team, passionate about diversity ;
  • Join a company with a true purpose – help us help our clients be more resilient towards climate risks;
  • A competitive salary, bonus and benefits;
  • You can benefit from a punctual home office days.

If you want to develop your skills and work in a friendly startup atmosphere, don’t hesitate and send us your application

At Descartes Underwriting, we cherish value of diversity whatever it may be. We are committed to fighting against all forms of discrimination and for equal opportunities. We foster an inclusive work environment that respects all differences.

With equal skills, all our positions are open to people with disabilities.

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