Data Analysis Engineer
Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. Avery Dennison scores B on the Alion truth index.
Avery Dennison Corporation (NYSE: AVY) is a global materials science and digital identification solutions company that provides branding and information labeling solutions, including pressure-sensitive materials, radio-frequency identification (RFID) inlays and tags, and a variety of converted products and solutions. The company designs and manufactures a wide range of labeling and functional materials that enhance branded packaging, carry or display information that connects the physical and the digital, and improve customers’ product performance. The company serves an array of industries worldwide, including home and personal care, apparel, e-commerce, logistics, food and grocery, pharmaceuticals and automotive. The company employs approximately 36,000 employees in more than 50 countries. Reported sales in 2022 were $9.0 billion. Learn more at www.averydennison.com.
Act as a technical support to the business team in Operations & Supply Chain, ensuring data solutions directly address the smart manufacturing roadmap and business priorities.
Deeply understand the operational pain points and business requirements of non-technical stakeholders and translate them into robust, technically feasible data architectures and digital solutions.
Design, build, and maintain scalable data pipelines to collect, ingest, clean, and aggregate raw data from diverse sources, including MES, SAP, and other shop-floor systems.
Ensure data quality, consistency, and reliability across the entire data lifecycle by implementing monitoring, validation, and error-handling mechanisms.
Support and enhance internal AI Agents and analytics tools by providing clean, well-structured data and maintaining data services that enable manufacturing insights and user support.
Digital Solutions & Automation: Collaborate to develop and deploy end-to-end digital solutions, such as automated workflows (Apps Script/Python) to optimize operational efficiency and reporting processes.
Team Enablement & Training: Assist in user onboarding and provide support/documentation for cross-functional teams to use self-service tools.
Bachelor's or Master’s degree in Engineering, or a related quantitative field.
Around 1-2 years of experience (including internships or part-time roles).
Core Competencies:
Solid knowledge of database design, data normalization, and data querying with SQL. Understanding of basic data analysis and processing workflows.
Relevant coursework or experience: programming techniques, data structures and algorithms, Python for Software Engineering.
Project experience: Have a graduation or internship project related to building data pipelines, web applications, or practical data management systems.
Background or coursework in manufacturing, industrial engineering, or supply chain data management systems.
Analytical mindset with strong logical thinking and eagerness to learn and adapt to new technologies.
Proficient in Google Workspace products (Sheets, Docs, etc.). Hands-on experience working with Gemini, Generative AI or agentic AI tools is a strong advantage.
Awareness of data security and privacy best practices.
Team-oriented, proactive, and self-motivated.