AWS Data Engineer (IoT Data Platform)

About the role

We are looking for an experienced AWS Data Engineer to join a European enterprise client building an IoT Data Platform. The role focuses on cloud‑native data engineering on AWS to support analytics, data products and machine‑learning use cases in an industrial IoT context.

Key responsibilities

• 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 optimise 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.

Required profile

• Hands‑on experience with AWS services such as Glue, Lambda, S3, Athena, Lake Formation, Step Functions, DynamoDB, IAM, Terraform and API Gateway.
• Strong data‑engineering background covering ETL pipeline development, data‑lake or data‑mesh architectures, schema and metadata management, and Python programming.
• Proficiency in PySpark for distributed processing and performance optimisation.
• Familiarity with modern data formats like Apache Iceberg and Parquet.
• Experience working in cross‑functional agile teams and participating in Scrum ceremonies.

Required skills

• AWS Glue
• AWS Lambda
• AWS S3
• AWS Athena
• AWS Lake Formation
• AWS Step Functions
• AWS DynamoDB
• AWS IAM
• Terraform
• AWS API Gateway
• Python
• PySpark
• Apache Iceberg
• Parquet