Google Cloud Platform data architect with Google MDE

Role : Google Cloud Platform data architect with Google MDE

Location : Chaska  (MN)/Aurora (IL) (Hybrid)

Contract

End client - Healthcare.

Experience - 13 years

Detailed JD: 

• Detailed JD:

Responsible for designing end-to-end data architectures that unify Industrial IoT (IIoT) data from the factory floor with enterprise IT systems. This role bridges the gap between operational technology (OT) and cloud-native analytics to drive use cases like predictive maintenance and quality anomaly detection.

Core Responsibilities

•€€€€€€ MDE Implementation: Design and implement the  to ingest, normalize, and store factory-floor data from diverse sources.

•€€€€€€ Solution Architecture: Define end-to-end Google Cloud Platform data architecture using BigQuery-centric patterns, GCS, Pub/Sub, and Dataflow for real-time and batch processing.

•€€€€€€ IT/OT Integration: Build architectures that connect MDE with the Cortex Framework to integrate manufacturing data with ERP (e.g., SAP) and CRM systems.

•€€€€€€ Use Case Enablement: Support the development of ML models for predictive maintenance, machine-level anomaly detection, and in-line quality control.

•€€€€€€ Governance & Security: Implement data security frameworks, IAM-based access control, and data governance strategies compliant with industry standards.

Required Skills & Experience

•€€€€€€ At least 14 years of experience, including 5 years as Google Cloud Platform data architect with hands on experience in Google MDE

•€€€€€€ Manufacturing Expertise: Deep understanding of manufacturing environments, including sensor data (noise, vibration, temperature) and OEE optimization.

•€€€€€€ Google Cloud Platform Data Stack: Proficiency in BigQuery, Cloud Storage, Dataflow, Dataproc, and Cloud Composer (Airflow).

•€€€€€€ Edge & IoT: Experience with Manufacturing Connect for edge-to-cloud data ingestion and handling streaming machine data.

•€€€€€€ Data Modeling: Expertise in designing conceptual, logical, and physical data models optimized for cloud performance and cost.

•€€€€€€ Programming: Strong SQL skills and proficiency in Python, Java, or Scala for pipeline development.

Preferred Qualifications

•€€€€€€ Google Professional Data Engineer or Professional Cloud Architect certification.

•€€€€€€ Experience with TimeSeries Insights API for real-time anomaly detection.

•€€€€€€ Background in integrating manufacturing hardware and managing global contract manufacturing partners