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Sr. Data Analytics Engineer

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Fecha: 15/05/2022

Ubicación: Reynosa, TAM, MX, 88730

Empresa: Corning

Sr. Data Analytics Engineer

Corning is one of the world’s leading innovators in materials science. For more than 160 years, Corning has applied its unparalleled expertise in specialty glass, ceramics, and optical physics to develop products that have created new industries and transformed people’s lives.

Corning succeeds through sustained investment in R&D, a unique combination of material and process innovation, and close collaboration with customers to solve tough technology challenges.

Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry. This segment is classified into two main product groupings – carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications. The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments, and individuals for their own use.


Sr.  Data Analytics Engineer

Molding Mfg. Data & Analytics (Digital transformation)

Reynosa, MX

Supervisor:  Process Engineering Manager


Position Description:

Serve as a process data analytics engineer for Molding Operations and any assigned extension within Molding Divisional Engineering.  Advance the state of Manufacturing 4.0 across the Molding organization through the expansion and usage of the Kairos platform and other data analytics tools.  The candidate will act as the process lead for the overall Data Analytics and Controls team, with Molding as the primary discipline supported.  He or she will become the Department SME regarding the structure and application of data analytics using the Kairos platform, as well as the tools used to retrieve, report and analyze data, with the primary objective to secure the usage of data as the main driver for continuous improvement activities.



  • Drive data analytics for assigned Areas
  • Drive strategical and tactical plans for data analytics and controls for assigned Areas
  • Serve as data analytics SME using data collection, data analysis, and machine learning tools
  • Build and deploy data-based models for use in process operational improvement
  • Leverage knowledge from company resources through direct support and communities of practice and collaborations
  • Provide guidance to other process engineers regarding data analytics best practices
  • Provide guidance to controls engineers regarding data analytics needs to link with hardware
  • Provide process direction and recommendations for data analytics and controls innovations
  • Identify areas of opportunity for data reporting, analysis, and machine learning model building
  • Review results and provide interpretation to ensure validity
  • Recommend additional data for collection, and linkages between data sets
  • Leverage corporate data analytics teams to impact assigned area, Plant, as needed
  • Utilize, Review and Create queries, dashboards, and graphical visualizations to access and report data
  • Coordinate with data science team on existing dashboards / graphical visualizations and create new ones
  • Become proficient in using no code / low code solutions to access data through the Databricks environment
  • Lead process improvement activities
  • Leverage data to determine improvement and paths for action
  • Design and execute experiments to enable data-based decisions
  • Implement solutions to improve cost, culture, capability and capacity


Travel Requirements: up to 15%

Hours of work:

  • Monday through Friday, 7:30am to 5pm as a base schedule.
  • Schedule will need to be flexed periodically to accommodate business/organization needs


Required Education:

  • Bachelor of Science in Engineering or equivalent
  • Master’s degree preferred
  • Instrumentation and Controls background will be a plus


Required Years and Area of Experience:

  • +5 years’ experience in plant engineering or an engineering support role to a manufacturing operation.
  • +3 years’ experience in a manufacturing operation under data science related role.


Required Skills:

  • Programming experience with python, R, or similar data analysis language and database querying such as SQL
  • Background in statistics and machine learning
  • Background in hand-on controls engineering (Problem solving)
  • Data Based Decision Making Skills with emphasis on data analysis, data visualization, and communication
  • Strong Problem-Solving Skills
  • Strong computer and data management skills
  • Bilingual (English/Spanish), Proficiency English skills


Process Discipline Specific Skills:

  • Strong skills in excel and SQL
  • Familiarity with JMP or Minitab
  • Familiarity with OSI PI
  • Bilingual (English/Spanish), English skills > 80%



Desired Skills:

  • Green Belt Certification or 6-Sigma Equivalent
  • Project leadership skills, including multi-cultural teams
  • Expertise in change management and documentation control systems
  • Understanding of Process Control and Process Discipline tools
  • Statistical tools such as statistical process control, hypothesis testing, sampling plans, capability analysis
  • Experimental design and analysis
  • Training in KT and MEE
  • Familiarity with Lean Manufacturing practices
  • Ability to engage with shop floor personnel and with plant leadership
  • Able to communicate through remote means (conference calls, email, IM)
  • Professional written and spoken communication