Smart Factory Data Engineering Architect (AWS/manufacturing) Job

Job Summary: -
Design and implement data architecture solutions for manufacturing and industrial environments. Build and manage data pipelines to collect and process data from IIoT devices, MES, SCADA, and ERP systems using AWS and Databricks. Integrate plant-floor systems like Ignition and ensure data quality, governance, and support for analytics and reporting

Key Responsibilities: -
* Design and implement data architecture solutions for manufacturing and industrial environments.
* Build and manage data pipelines to collect and process data from IIoT devices, PLCs, MES, SCADA, historians, and ERP systems.
* Develop and maintain cloud-based data platforms using AWS and Databricks for data storage, processing, and analytics.
* Integrate plant-floor systems like Ignition into centralized data platforms and support real-time and batch data processing for production insights.
* Ensure data quality, security, governance, and proper documentation, while working with OT, IT, and business teams to support analytics, machine learning, and reporting

Required Qualifications: -
* Bachelor’s degree in Computer Science, Engineering, or a related field with knowledge of Unified Name Space (UNS) modeling.
* 7+ years of experience in data architecture or data engineering, especially in manufacturing or smart factory environments.
* Hands-on experience with Databricks, along with strong skills in SQL, Python, and Spark for data processing and analytics.
* Good knowledge of AWS services such as S3, Glue, Lambda, Redshift, RDS, IAM, and IoT Core.
* Experience working with IIoT data and integrating systems like MES, SCADA, ERP, and historians using protocols like OPC UA, MQTT, or Modbus.
* Understanding of data modeling, ETL/ELT pipelines, lakehouse architecture, data governance, and visualization tools like Power BI or Tableau (AWS or Databricks certification is a plus).