Job description:
Experience: 2-5 years, 6-8 years, 9+
Location: Paris, Bordeaux
Job Overview
QUANT AI Lab is seeking a passionate and experienced Data Engineer capable of designing, building, and optimizing modern data management infrastructures. You will work on strategic projects, leveraging the latest Cloud, Big Data, and containerization technologies. You will actively contribute to transforming data into performance drivers for our clients while collaborating with multidisciplinary teams.
Responsibilities
Design and Deployment of Cloud Data Infrastructures:
– Develop and maintain secure, reliable, and scalable Cloud solutions (AWS, Azure, or GCP).
– Automate deployments using Infrastructure as Code (IaC) tools like Terraform, CloudFormation, or Pulumi.
Building and Optimizing Data Pipelines:
– Create efficient ETL pipelines to process both structured and unstructured data.
– Ensure the reliability, performance, and optimization of massive data flows.
CI/CD Process Automation:
– Configure and automate CI/CD pipelines using tools like GitHub Actions, Jenkins, or GitLab CI/CD.
– Ensure fast and secure deliveries through best practices in CI/CD.
Database Management and Big Data Tools:
– Design, optimize, and maintain relational (SQL) and NoSQL (MongoDB, DynamoDB, etc.) databases.
– Work with Big Data frameworks like Apache Spark, Hadoop, Kafka, or Flink for processing large datasets.
Containerization and Orchestration:
– Deploy and manage containers with Docker, and orchestrate them using Kubernetes.
– Ensure the efficiency and scalability of containerized solutions.
Interdisciplinary Collaboration:
– Work closely with Data Scientists, DevOps Engineers, and Product Owners to ensure project success.
Your profil
Education: Master’s degree in Computer Science, Software Engineering, Applied Mathematics, or a related field.
Technical Skills:
– Cloud Computing: Expertise in AWS, Azure, or GCP.
– Infrastructure as Code: Proficiency in Terraform, CloudFormation, or Pulumi.
– Big Data: In-depth knowledge of Spark, Hadoop, Kafka, or Flink.
– Programming Languages: Strong command of Python, Scala, or Java.
– Databases: Expertise in SQL and NoSQL (MongoDB, Cassandra, etc.).
– CI/CD: Experience with pipeline automation tools (GitHub Actions, Jenkins, etc.).
– Containerization: Mastery of Docker and Kubernetes.
– Data Security: Knowledge of best practices for data processing and storage security.
Experience:
– 2 to 5 years of professional experience as a Data Engineer or in a similar role.
– Experience in a DevOps or Agile environment is a plus.
– Cloud certifications (AWS Certified Solutions Architect, Google Cloud Professional Data Engineer, etc.) are an advantage.
Personal Skills:
– Analytical mindset and problem-solving skills.
– Ability to work in a team in a multicultural and dynamic environment.
– Proactive with a curiosity for new technologies.
– Excellent communication skills and the ability to simplify technical concepts.
