Data Architect; Manufacturing

Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.

We are looking for an experienced SCADA & Data Architect to design and implement industrial data architectures that integrate SCADA (Ignition), IoT, Unified Namespace (UNS), and cloud data platforms
. The ideal candidate will have hands-on experience with Ignition SCADA, HiveMQ (UNS), Azure Data Factory, and Snowflake
, ensuring seamless data flow, scalability, and real-time analytics across industrial systems.

• Design, develop, and optimize SCADA (Ignition) and IoT data architectures for industrial automation.
• Implement Unified Namespace (UNS) using HiveMQ to enable real-time data streaming and interoperability.
• Integrate SCADA and IoT data pipelines with Azure Data Factory and Snowflake for efficient storage, processing, and analytics.
• Develop robust data ingestion, transformation, and processing workflows for industrial systems.
• Ensure high availability, security, and scalability of industrial data platforms.
• Work with MQTT, OPC UA, and other industrial communication protocols for seamless data exchange.
• Collaborate with cross-functional teams to optimize industrial data workflows and analytics
  .
• Provide technical leadership and best practices for SCADA, IoT, and cloud data integration
  .

• Strong experience with Ignition SCADA for industrial automation and control systems.
• Hands‑on expertise with HiveMQ and Unified Namespace (UNS) for IoT and data streaming.
• Experience in designing and implementing Azure Data Factory workflows.
• Proficiency in Snowflake for industrial data storage, ETL, and analytics.
• Knowledge of MQTT, OPC UA, and industrial IoT protocols
  .
• Experience with real‑time data processing and event‑driven architectures
  .
• Strong understanding of industrial data modeling, pipelines, and cloud integration
  .
• Proficiency in Python, SQL, or scripting languages for data processing.

• Experience with edge computing and IoT gateways
  .
• Knowledge of cybersecurity best practices for industrial data architectures.
• Familiarity with Dev Ops/MLOps practices for data pipeline automation.