Manufacturing Data Architect

Job Summary

We are seeking an experienced Manufacturing Data Architect to design, build, and scale modern data platforms that power smart manufacturing, industrial analytics, and connected operations. This role will lead the architecture of data solutions across plant systems, IIoT devices, SCADA/MES platforms, and cloud environments, with a strong focus on Databricks, AWS, and Ignition. The ideal candidate has deep experience in manufacturing data ecosystems and understands how to transform raw machine, sensor, and operational data into reliable, secure, and business-ready insights. This person will work closely with manufacturing, operations, engineering, and IT teams to create an industrial data backbone that supports real-time visibility, predictive analytics, and digital transformation initiatives.

Key Responsibilities Design and implement enterprise-scale data architecture for manufacturing and industrial environments Build and optimize data pipelines that ingest data from IIoT devices, PLCs, historians, MES, SCADA, and ERP systems Architect and manage cloud-based data solutions using AWS services and Databricks Integrate plant-floor systems, especially Ignition, into centralized data platforms for analytics and reporting Develop scalable data models, lakehouse architectures, and governance frameworks for manufacturing data Enable real-time and batch data processing for use cases such as OEE, downtime analysis, predictive maintenance, quality monitoring, and production performance Establish standards for data quality, security, lineage, and master data management across operational and enterprise systems Collaborate with plant engineers, OT teams, IT teams, and business stakeholders to align architecture with operational goals Support advanced analytics, machine learning, and dashboarding initiatives by ensuring clean, accessible, and trusted data Document architecture, integration patterns, and best practices for ongoing platform support and expansion





Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field Good understanding of Unified Name Space (UNS) Modelling. 7+ years of experience in data architecture, data engineering, or industrial data solutions Strong experience in manufacturing, industrial, or smart factory environments Hands-on experience with Databricks for data engineering, transformation, and analytics Strong knowledge of AWS services such as S3, Glue, Lambda, Redshift, RDS, IAM, IoT Core, or related tools Experience working with IIoT data, industrial protocols, and manufacturing systems Hands-on experience with Ignition for industrial data connectivity, visualization, or system integration Strong understanding of data modeling, ETL/ELT pipelines, lakehouse architecture, and distributed data processing Experience integrating data from systems such as MES, SCADA, historians, ERP, and CMMS Proficiency in SQL, Python, and Spark Strong understanding of data governance, security, and compliance in enterprise environments

Preferred Qualifications Experience with manufacturing KPIs such as OEE, yield, scrap, cycle time, downtime, and throughput Familiarity with industrial protocols such as OPC UA, MQTT, Modbus, or ISA-95 Experience with streaming or real-time data architectures Knowledge of machine learning or predictive analytics in industrial settings Experience with visualization tools such as Power BI, Tableau, or Databricks dashboards AWS or Databricks certifications are a plus Experience working across both OT and IT environments

Key Skills Manufacturing data architecture IIoT and industrial connectivity Databricks and Spark AWS cloud architecture Ignition platform integration Data modeling and pipeline design Real-time and batch processing Cross-functional collaboration Data governance and security

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