IT Manufacturing Data Engineer

Elanco•Indianapolis, IN

10h•Hybrid

About The Position

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 will specialize 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. This includes four strategic priorities : Pipeline Acceleration: Optimize 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.

Requirements

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 essential, preferably within a GxP -regulated industry such as pharmaceuticals, biologics, or animal health.
OEE Expertise: A strong understanding of Overall Equipment Effectiveness (OEE) principles, the underlying metrics, and how they are applied in a manufacturing context.
Strong Analytical Skills: Proven ability to work with large datasets, perform quantitative analysis, and identify meaningful trends and correlations that drive business value.
Data Visualization Tools: Proficiency with data visualization software such as Power BI or Tableau to create effective, user-friendly dashboards and reports.
Data Handling Skills: Strong skills in Microsoft Excel are a must . Proficiency in SQL for querying data from databases is highly desired.
Familiarity with Manufacturing Systems: Experience with or exposure to data from systems like MES, SCADA, or Data Historians (e.g., OSI PI) is a significant plus.
Problem-Solving Mindset: A curious and methodical approach to problem-solving, with a passion for digging into data to uncover the "why" behind performance issues.
Communication Skills: The ability to communicate data-driven insights clearly and concisely to both technical and non-technical audiences.

Nice To Haves

Cloud and DevSecOps Familiarity : Familiarity with cloud platforms (Azure or GCP) and DevSecOps concepts.

Responsibilities

OEE Analysis & Reporting: Be responsible for the process of collecting, analyzing, 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: Analyze 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 Optimization: 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.