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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Principle Manufacturing Data Architect - **Company:** Alcon Inc - **Location:** Fort Worth, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Cyber Security, Data as a Services, Data Architecture, Extract Transform Load (ETL), Middleware, Supervisory Control and Data Acquisition (SCADA), Machine Learning, Message Queuing Telemetry Transport (MQTT), OPC Unified Architecture, Data Streaming, Technical Data Management Systems, Google Cloud, Cloud Platform System, Data Lakes, Data Management, Restful APIs, Data Pipelines - **Published:** August 2, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/86913628/1 ## About the Role * Bachelor's Degree or Equivalent years of directly related experience (or high school +15 yrs; Assoc.+11 yrs; M.S.+4 yrs; PhD+3 yrs) * The ability to fluently read, write, understand, and communicate in English * 7 Years of Relevant Experience * 5 Years of Demonstrated Leadership, * Strong understanding of manufacturing systems and automation, including PLCs, SCADA, historians, MES, and ERPs. * Hands-on experience with industrial data protocols and platforms (e.g., OPC UA, MQTT, REST APIs). * Experience building or governing contextualized manufacturing data models. * Familiarity with cloud platforms (Azure, AWS, GCP) and data services (data lakes, streaming, analytics). * Experience enabling or collaborating on AI/ML solutions for manufacturing. * Understanding of industrial cybersecurity principles and IT/OT security boundaries. * Experience with time-series data analytics, visualization, and alerting. * Understanding of predictive maintenance, reliability analytics, and process optimization. * Familiarity with digital twin concepts and closed-loop optimization strategies. * Ability to translate complex technical concepts into business value. ## Description * Define and own the global OT data architecture strategy, including data acquisition, middleware, historian strategy, contextualization layers, and data pipelines. * Select and standardize industrial data platforms, protocols, and middleware (e.g., OPC UA, MQTT, historians, industrial edge platforms). * Ensure secure, reliable, and scalable data movement from OT to IT and cloud environments in alignment with corporate cybersecurity policies. * Establish reference architectures and implementation patterns for manufacturing sites globally. Data Contextualization, Governance & Standardization * Lead development of global data models, asset hierarchies, naming conventions, and contextualization frameworks. * Own governance processes to ensure data consistency across sites, equipment types, and process technologies. * Enable reuse of analytics by ensuring that similar assets and processes generate comparable, high-quality data. * Partner with manufacturing, engineering, and IT teams to drive adherence to standards while allowing necessary local flexibility. Analytics, Insights & Value Creation * Drive development of analytics enablement layers that support dashboards, trending, alerting, and anomaly detection. * Collaborate with data scientists and operations teams to deploy AI/ML models for manufacturing use cases. * Translate manufacturing pain points into data-driven insights and actionable intelligence. * Enable systematic identification of OEE improvements across diverse equipment and processes. Advanced Manufacturing Intelligence * Support the assessment and creation of state-of-the-art industrial analytics technologies that scale, including: + Predictive and prescriptive maintenance + Process optimization and digital twins + Closed-loop control and automated decision-making * Partner with controls engineers and operations to integrate analytics outputs into automated or semi-automated control strategies. * Drive roadmap development for advanced manufacturing intelligence capabilities. Global Leadership & Collaboration * Serve as a technical leader and subject matter expert across a global manufacturing network. * Collaborate with Manufacturing, Automation, IT, Cybersecurity, Data Science, and Cloud teams. * Support site deployments, scaling successful pilots into sustainable global solutions. * Mentor engineers and influence technical direction without direct authority where applicable. ## Related Videos - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Developer’s Perspective: Overview of the Tezos Blockchain Ecosystem](https://www.wearedevelopers.com/videos/237-developer-s-perspective-overview-of-the-tezos-blockchain-ecosystem) - [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) - [Exploring BOS: The Blockchain Operating System by NEAR Protocol](https://www.wearedevelopers.com/videos/781-exploring-bos-the-blockchain-operating-system-by-near-protocol) - [REST In Peace: Why LLMs Can't CRUD](https://www.wearedevelopers.com/videos/100272-rest-in-peace-why-llms-can-t-crud) ## Related Articles - [Now is the time for industrialized software development](https://www.wearedevelopers.com/magazine/601-now-is-the-time-for-industrialized-software-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)