Data Engineer

Responsibilities: - Design, build, and maintain scalable data platforms. - Collect, process, and analyze large and complex data sets from various sources. - Develop and implement data processing workflows using data processing framework technologies such as Spark, and Apache Beam. - Collaborate with cross-functional teams to ensure data accuracy and integrity. - Ensure data security and privacy through proper implementation of access controls and data encryption. - Extraction of data from various sources, including databases, file systems, and APIs. - Monitor system performance and optimize for high availability and scalability. Requirements: - Experience with cloud platforms and services for data engineering (GCP). - Proficiency in programming languages like Python, Java, or Scala. - Use of Big Data Tools such as Spark, Flink, Kafka, Elastic Search, Hadoop, Hive, Sqoop, Flume, Impala, Kafka Streams and Connect, Druid, etc. - Knowledge of data modeling and database design principles. - Familiarity with data integration and ETL tools (e.g., Apache Kafka, Talend). - Understanding of distributed systems and data processing architectures. - Strong SQL skills and experience with relational and NoSQL databases. - Familiarity with cloud platforms and services for data engineering (e.g., AWS S3, Azure Data Factory). - Experience with version control tools such as Git. - Ability to adapt to different contexts, teams and Clients. - Teamwork skills but also sense of autonomy. - Motivation for international projects and ok if travel is included. - Willingness to collaborate with other players. - Strong communication skills.