Data Engineer

You will join the Data Platform team as a Data Engineer and you will be responsible for building, optimizing, and maintaining data pipelines and infrastructure to support scalable data processing and storage. This includes designing data architectures, ensuring efficient data flow, and enabling easy access to data for analytics and machine learning applications. You will work closely with other engineers, data scientists, and product teams to ensure data quality, security, and integration with cloud technologies, facilitating a reliable and flexible data ecosystem that supports the platform’s growth and functionality.

Responsibilities

• Define and analyze data structures
• Design, build, and manage ETL (Extract, Transform, Load) pipelines that ingest raw data from various sources, transform it, and load it into data warehouses or lakes
• Design and manage storage solutions, such as data warehouses (Amazon Redshift), data lakes (AWS S3 with Databricks), or NoSQL databases
• Work closely with data scientists, analysts, and business teams to understand data needs, gather requirements
• Ensure production reliability (monitoring, alerting, and intervene as needed)
• Experiment with emerging data technologies and best practices to enhance data infrastructure and workflow efficiency

Qualifications

• Master's degree (BAC+5), you have at least 4 years of experience as a Data Engineer
• Advanced expertise in Python is essential, with strong skills in Java (Spring Boot), and familiarity with Scala being a plus
• Proficiency in ETL processes and data pipelines
• Hands-on experience in building, managing, and optimizing data workflows on Databricks, including the use of Spark for large-scale data processing
• Expertise in storage solutions (object storage / relational databases / NoSQL)
• At least one professional experience with the AWS public cloud
• Experience working in an agile environment and commitment to agile principles

Additional Skills

• Upper-Intermediate English level and ability to communicate effectively
• Strong adaptability and flexibility
• Keen to work in an Agile/SAFE environment
• Strong team spirit, supportive of others’ contributions