IT Manufacturing Data Engineer

At Elanco (NYSE: ELAN) – it all starts with animals!

As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.
At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.

At Elanco, we pride ourselves on fostering a diverse and inclusive work environment. We believe that diversity is the driving force behind innovation, creativity, and overall business success. Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.

Making animals’ lives better makes life better – join our team today!

Driven by the quickening pace of innovation, Animal Health is on the verge of a revolution, powered by digital business models, technology and data.

Elanco IT is a catalyst for change, partnering to identify and deliver transformative solutions to solve our biggest business problems.

This includes four strategic priorities:

• Pipeline Acceleration:
  Optimise the search and approval of high impact medicines with a focus on speed, cost and precision.
• Manufacturing Excellence:
  Improve the efficiency, quality and consistency of core manufacturing processes, specifically execution and equipment effectiveness.
• Sales Effectiveness:
  Simplify the process to find, trust and consume relevant customer insights that drive sales growth and improved engagement.
• Productivity:
  Expand operating margin through efficiency by systematically reducing our operating expenses across the company, improving profitability.

As a Manufacturing Data Engineer at Elanco, you will be the analytical engine driving operational excellence across our production sites.

Reporting to the Engineering team, you specialise in transforming production data into insights that improve our Overall Equipment Effectiveness (OEE).

This role is perfect for a data-driven individual who is passionate about finding actionable insights within complex manufacturing data to increase efficiency, improve product yield, and enhance quality and compliance.

• OEE Analysis & Reporting: Be responsible for the process of collecting, analysing, and reporting on OEE metrics (Availability, Performance, Quality) for critical production lines. You will develop and maintain dashboards and reports that provide clear, timely visibility into equipment performance for the operations teams.

• Identify Improvement Opportunities: Analyse manufacturing data from systems like MES, SCADA, and Data Historians to identify the primary causes of production losses, such as equipment downtime, slow cycle times, and yield loss.

• Support Data-Driven Decisions: Translate complex datasets into clear, actionable insights and recommendations. Your analysis will help guide the continuous improvement efforts of our manufacturing and engineering teams.

• Support Root Cause Analysis: Provide data and analytical support for deviation investigations and root cause analysis exercises related to production losses and quality events, helping to ensure robust corrective and preventative actions (CAPAs).

• Data Integrity and Systems: Partner with Automation and IT teams to ensure the accuracy and integrity of data captured from our manufacturing systems, ensuring it aligns with GxP and ALCOA+ principles.

• Process Optimisation: Collaborate with process engineers and operations teams to monitor the impact of process changes and validate the effectiveness of improvement initiatives by quantifying the results.

• Communicate Findings: Clearly present analytical findings, trends, and recommendations to various stakeholders, from shop-floor teams to site leadership, in a way that is easy to understand and act upon.

• Educational Background: A Bachelor's degree in Engineering, Statistics, Data Analytics, or a related quantitative field.
• Manufacturing
  
  Experience:
  
  Experience working in a manufacturing environment is…