Ignition Architect

Zeus Industrial Products, Inc.•Orangeburg, SC

About The Position

The Ignition Architect position is a senior individual contributor responsible for designing, integrating, and scaling industrial automation, SCADA, and manufacturing data systems across manufacturing operations. This role operates at the intersection of controls engineering, Ignition SCADA/MES, enterprise data platforms, cloud and on-prem infrastructure, and applied machine learning, providing technical leadership and architectural direction without direct people management. The SCADA Architect serves as a technical authority and escalation point for complex automation, data and infrastructure challenges, driving standardization, reliability, and long-term scalability across plant-floor and enterprise systems.

Requirements

Bachelor’s degree in Electrical Engineering, Computer Engineering, or related field (or equivalent experience)
10+ years of experience in industrial automation, controls engineering, or manufacturing systems
Strong expertise in PLC programming, industrial networking, drives, and motion control
Advanced experience with SCADA platforms, particularly Ignition
Proficiency in Python for automation, data processing, and system integration
Experience with relational databases and database administration in manufacturing environments
Hands-on experience with Linux and Microsoft OS on hybrid infrastructure environments
Strong understanding of OT/IT integration, cybersecurity considerations, and system reliability

Nice To Haves

Experience deploying machine learning or edge AI solutions in production manufacturing environments
Familiarity with Snowflake or similar enterprise analytics platforms
Experience with Nutanix, AWS or VMWARE infrastructure in hybrid cloud/on-prem deployments
Familiarity with containerized workloads and edge computing architectures
Experience with high-speed, continuous, or tightly tolerance manufacturing processes
Background in designing enterprise-scale automation, SCADA, or MES platforms
Experience influencing technical strategy across multiple sites or cross-functional teams

Responsibilities

Design and maintain end-to-end automation architectures spanning PLCs, drives, motion systems, and safety-critical control environments
Develop scalable control strategies for high-speed and continuous manufacturing processes
Define standards and best practices for control system design, versioning, testing, and lifecycle management
Architect, support, and evolve SCADA and MES platforms, with deep expertise in Ignition-based systems
Design and maintain tag models, historian strategies, alarming frameworks, and visualization standards
Ensure high availability, performance, and maintainability of plant-floor data systems
Establish consistent data models and interfaces between SCADA/MES and enterprise analytics platforms
Deep knowledge of the Ignition WebDev Module, developing and publishing REST APIs, and building and documenting OpenAPI 3.0.0 specifications. Hands-on experience with load balancers such as NGINX.
Integrate plant-floor systems with enterprise databases and analytics platforms, including Snowflake
Design and support secure OT/IT data pipelines leveraging AWS services and hybrid architectures
Collaborate with infrastructure teams supporting cloud and on-prem platforms, including AWS, Nutanix-based and VMWARE-based environments
Support Linux-based edge systems, containerized services, and automation-related infrastructure
Align automation systems with enterprise security, networking, and infrastructure standards
Provide hands-on database administration (PostGres, MsSQL) for manufacturing and automation systems, including schema design, performance tuning, backup/recovery, and data integrity
Support operational reliability of relational databases used by SCADA, MES, and analytics workloads
Partner with IT and data teams to ensure manufacturing data is accurate, accessible, and governed
Design and deploy edge AI and machine learning inference pipelines for manufacturing use cases such as anomaly detection, predictive quality, and process optimization
Develop and maintain Python-based services for data processing, feature extraction, and model inference
Ensure AI-enabled solutions meet real-time, latency, reliability, and operational constraints of industrial environments
Serve as a technical escalation point for complex automation, data, performance, and integration issues
Lead technical design reviews and influence platform, architecture, and vendor decisions
Mentor engineers and provide guidance on advanced automation, SCADA, data, and edge AI topics
Translate manufacturing, quality, and operational requirements into scalable, supportable technical solutions
Drive continuous improvement initiatives that increase system uptime, data reliability, and operational efficiency