AWS Data Engineer – Manufacturing & Unified Namespace (UNS)

Job Summary

We are seeking an experienced AWS Data Engineer to design build and support cloud-based data pipelines for manufacturing and industrial systems. The ideal candidate will have strong expertise in real-time data engineering AWS cloud services and Unified Namespace (UNS) architectures to enable scalable data integration across shop-floor systems Digital Twin platforms and analytics solutions.

This role will focus on ingesting standardizing and delivering manufacturing data from presses sensors CBM systems MES platforms and manual inputs into enterprise data and analytics environments.

Key Responsibilities

• Design and implement cloud-based data ingestion pipelines from manufacturing systems including PLCs press controllers CBM systems and MES platforms.
• Publish and consume industrial data through MQTT-based Unified Namespace (UNS) architectures.
• Build scalable real-time near real-time and batch data pipelines on Amazon Web Services.
• Transform and model raw machine and operational data into contextualized asset-based datasets.
• Integrate manufacturing data into Digital Twin analytics reporting and KPI calculation platforms.
• Ensure high levels of data quality reliability observability and pipeline performance.
• Collaborate with engineering manufacturing and analytics teams to support industrial data initiatives.
• Maintain documentation and support best practices for industrial data architecture and governance.

Required Qualifications

• Strong hands-on experience with Python for data engineering and pipeline development.
• Proficiency in SQL for analytics transformations and data processing.
• Experience with stream and batch processing architectures.
• Strong understanding of MQTT publish/subscribe communication patterns.
• Experience designing topic namespaces aligned with industrial asset hierarchies.
• Hands-on experience implementing or consuming Unified Namespace (UNS) architectures.
• Experience working with JSON Avro and Parquet data formats.
• Strong analytical troubleshooting and problem-solving skills.

Preferred Qualifications

• Experience with manufacturing or industrial IoT environments.
• Exposure to Digital Twin architectures and industrial analytics platforms.
• Familiarity with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
• Experience with AWS-native data services and cloud data architectures.
• Understanding of MES CBM and shop-floor integration concepts.

Key Skills & Competencies

• AWS Cloud Data Engineering
• MQTT & Unified Namespace (UNS)
• Real-time & Streaming Data Pipelines
• Industrial IoT & Manufacturing Data
• Python & SQL Development
• Data Modeling & Transformation
• Data Quality & Observability
• Analytics & Digital Twin Integration