Intermediate/Senior Data Engineer - Scientific Engine

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 🗺️).