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ASR Group/Domino Sugar Sr. Data Manufacturing Engineer in Baltimore, Maryland

ASR Group is the world’s largest refiner and marketer of cane sugar, with an annual production capacity of more than 6 million tons of sugar. The company produces a full line of grocery, industrial, food service and specialty sweetener products. Across North America, ASR Group owns and operates six sugar refineries, located in Louisiana, New York, California, Maryland, Canada and Mexico. In the European Union, the company owns and operates sugar refineries in England, Portugal. ASR Group also owns and operates mills in Mexico and Belize. The company’s brand portfolio includes the leading brands Domino®, C&H®, Redpath®, Tate & Lyle®, Lyle’s® and Sidul®

Overview

This position will manage databases and SCADA solutions. The role involves integrating data from various sources, including SAP and other systems, while ensuring the validity and integrity of the data. In addition, the candidate will also be responsible for developing and optimizing SCADA and manufacturing solutions. A significant part of the role involves building innovative solutions for manufacturing optimization using AI/ML techniques and process simulations.

Responsibilities

  • Develop and maintain corporate production website using Web Server technologies and .Net, ensuring a smooth integration of production data and other relevant information.

  • Develop and maintain MSSQL data solutions, refine SQL queries and objects, and enhance database performance and security.

  • Validate and integrate data from SAP and other sources to ensure quality and consistency.

  • Integrate and optimize industrial automation systems using Wonderware Systems Platform & OSI PI Historian Platforms.

  • Perform data analysis, modeling, and scripting using Python and Matlab to support various projects.

  • Build datapiplines and asset frameworks in OSI PI and Datahub

  • Apply advanced analytics AI/ML techniques to develop predictive and prescriptive quality and maintenance solutions

  • Analyze data and models to provide actionable insights and recommendations.

  • Collaborate with cross-functional teams to design and implement data science projects aimed at improving manufacturing processes.

  • Integrate process modeling techniques with control systems to improve overall plant performance.

  • Stay updated with the latest advancements in data science, advanced analytics, and manufacturing technologies.

    Qualifications

  • Demonstrated experience in MSSQL, Web Server technologies, and .Net programming.

  • Proficiency in Wonderware Systems Platform SCADA, and Data Historian (AVEVA PI).

  • Strong programming skills in Python and Matlab.

  • Advanced knowledge of Power BI for data visualization.

  • Familiarity with AVEVA Data Hub, predivtice and advance analytics tools.

  • Familiarity with advanced analytics, including predictive and prescriptive maintenance tools.

  • Solid understanding of data science principles and methodologies.

  • Proficient knowledge of AI and ML algorithms, tools, and practices, with practical experience in integrating these technologies into control systems.

  • Proficient in ControlLogix

    Required Education and Work Experince

  • Bachelor’s degree in Chemical, Computer, Electrical or Mechnical Engineering

  • 5+ years of work experience in Process Control System and SCADA Solutions in manufacturing.

    Preferred Qualifciation and Education

  • Allen Bradley PLC ControlLogix

  • AVEVA Saas Solutions for process simulation & analytics

  • Master in Data Science

    Supervisory Responsibilites

  • None

    Travel Requiements

  • 20% travel (domestic)

    Location

    Must be located at one of our refineries in Baltimore, Chalmette, Crockett, Yonkers

We are an equal opportunity employer. We do not discriminate on the basis of race, color, creed, religion, gender, sexual orientation, gender identity, age, national origin, disability, veteran status or any other category protected under federal, state, or local law. All employment is decided on the basis of qualifications, merit, and business need.

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