Sr. Principle Global Industrial Analytics Engineer

Alcon Research•Fort Worth, TX

10h•Hybrid

About The Position

At Alcon, we're passionate about enhancing sight and helping people see brilliantly. With more than 25,000 associates, we innovate fearlessly, champion progress, and act swiftly to impact global eye health. We foster an inclusive culture, recognizing your contributions and offering opportunities to grow your career like never before. Together, we make a difference in the lives of our patients and customers. Are you ready to join us? We foster an inclusive culture and are looking for diverse, talented people to join Alcon. Alcon has ambitious plans to blend modern manufacturing technologies with digital technologies. This position will serve as a global technical authority for manufacturing data system architecture, analytics enablement, and advanced industrial intelligence. This role is responsible for defining, standardizing, and governing the OT data architecture and technology stack, ensuring manufacturing data is moved from shop-floor OT systems into IT and cloud environments. This position will establish global data contextualization standards and governance, enabling scalable analytics, AI/ML solutions, dashboards, and predictions across similar sites, assets, and process types. The role will drive the development of insight-generating capabilities—including trending, alerting, and optimization—while continuously evaluating and deploying state-of-the-art technologies to enable advanced use cases such as predictive maintenance, automated diagnostics, and closed-loop process control. A key aspect to the role will require close collaboration across multiple local/global functions including engineering, data science, data engineering, and IT teams. Direct manufacturing experience is required to ensure practical systems and solutions are defined and implemented which meet the needs of manufacturing teams.

Requirements

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

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.
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.