Data Engineer

ThunderSoft; Paris; Sur place; EUR 85 000 - 120 000; Plein temps

Résumé du poste

ThunderSoft is seeking a Data Engineer in Paris to build, optimize, and maintain data pipelines and infrastructure for scalable analytics and ML applications.

You will design data architectures, ensure data quality, and enable secure access while working with cloud technologies to support our platform's growth and functionality.

Qualifications

• Master's degree (BAC+5) required; 4+ years experience as a Data Engineer.
• Strong Python expertise; Java Spring Boot strong; Scala optional.

Responsabilités

• 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 data lakes.
• Design and manage storage solutions (data warehouses, data lakes, NoSQL).
• Collaborate with data scientists, analysts, and business teams to understand data needs and gather requirements.
• Ensure production reliability via monitoring and alerting; intervene as needed.
• Experiment with emerging data technologies to enhance data infrastructure and workflow efficiency.

Connaissances

Python

Java Spring Boot

Scala

ETL processes

Data pipelines

Databricks

Spark

AWS

Agile

Team collaboration

Formation

Master's degree (BAC+5)

Outils

Databricks

Spark

AWS

Description du poste

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.

• 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.
• 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