About this role

Develop and optimize high-performance data pipelines.
Design scalable solutions for processing large volumes of data.
Contribute to the definition and evolution of the data architecture.
Implement ETL processes and integration across multiple data sources.
Work with distributed systems and event-driven architectures.
Ensure data quality, performance, and reliability.
Integrate data platforms with applications and APIs.
Participate in technical discussions and support the evolution of engineering best practices.

Bachelor's degree in Computer Science, Engineering, Information Systems or related fields.
Advanced English for oral and written communication.
Excellent communication and collaboration skills across technical and business teams.
Minimum of 7 years of professional experience in Technology.
At least 5 years of hands-on experience as a Data Engineer using Apache Spark.
Mandatory Technical Knowledge
Data Engineering
ETL/ELT
Apache Spark
PySpark
Distributed data processing
Data modeling and integration
Messaging and Streaming
Apache Kafka
Real-time event processing
Databases
Relational databases (SQL)
NoSQL databases
Architecture and Platform
System Architecture
Distributed Systems
REST APIs
Cloud Computing
Application integration

Senior Data Engineer, Spark

Key skills