PI Historian Engineer

We are looking for a skilled PI Historian Engineer with hands-on experience in AVEVA PI System and cloud integration, particularly with Google Cloud Platform (Google Cloud Platform). In this role, you will be responsible for designing, implementing, and maintaining real-time data infrastructure to support critical operations and analytics initiatives. You will also be a key contributor to our digital transformation journey, enabling scalable, cloud-connected operational intelligence.

Key Responsibilities:

• Design, configure, and maintain AVEVA PI System components (PI Data Archive, PI Asset Framework, PI Vision, PI Interfaces/Connectors).
• Lead the integration of PI System data with Google Cloud Platform (e.g., BigQuery, Cloud Pub/Sub, Dataflow) to enable advanced analytics, visualization, and AI/ML workflows.
• Develop and manage data pipelines to extract, transform, and load PI data into cloud-based data lakes and analytical platforms.
• Support end users by developing PI Vision dashboards, PI AF templates, and event-based analytics.
• Collaborate with data engineering, IT, and operations teams to ensure data accuracy, timeliness, and availability across systems.
• Perform system upgrades, patching, and performance tuning for PI components.
• Ensure compliance with data governance, cybersecurity, and regulatory standards.
• Troubleshoot historian data flow, interface connectivity, and system reliability issues.

Required Qualifications:

• Bachelor’s degree in Engineering, Computer Science, Industrial Automation, or a related field.
• 3+ years of experience working with AVEVA PI System (or OSIsoft PI), including configuration, administration, and troubleshooting.
• Experience integrating PI System with Google Cloud Platform tools such as:
  • BigQuery
  • Pub/Sub
  • Cloud Functions
  • Dataflow or Dataproc
• Familiarity with industrial protocols (OPC DA/UA, Modbus, MQTT) and data acquisition systems.
• Proficiency in scripting languages such as PowerShell, Python, or SQL for automation and integration.
• Strong understanding of time-series data, historian architectures, and operational technology (OT) environments.