AWS Data Engineer
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- Design, implement and operate cloud-native data pipelines on AWS for the IoT Data Platform
- Build and maintain scalable ETL workflows, data lakes and data mesh components using modern data formats and processing frameworks
- Develop and optimize distributed data processing jobs in PySpark for large-scale and time-series workloads
- Design and manage data schemas, tables and metadata using AWS Glue Data Catalog and Lake Formation Must-have skills
- Hands-on AWS: Glue, Lambda, S3, Athena, Lake Formation, Step Functions, DynamoDB, IAM, Terraform, API Gateway
- Data engineering: ETL pipeline development, data lakes and/or data mesh architectures, schema and metadata management, Python
- Data processing: PySpark for distributed processing and performance optimization
- Data formats: Apache Iceberg and Parquet
- Experience in cross-functional agile teams and Scrum ceremonies Nice to have
- Practical experience with time-series data, ideally from industrial machines or similar IoT sources
- Basic understanding of ML/AI concepts, governance principles and MLOps (lifecycle management, pipelines, CI/CD)
- AWS API Gateway, data exchange and integration APIs
- CI/CD pipelines, containerization, automated deployment and testing Setup Full-time, based in Tunis, embedded with the client's engineering team.
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