1d ago
Data Analysis Engineer
Averydennison is the employer — EngRadar is a job radar, not a recruiter. We track this posting from their own careers page and send you straight there; we never handle applications or CVs.
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.
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