Analyze complex datasets to identify trends, patterns, and opportunities that drive business insights and operational improvements.
Collaborate with business and technical teams to gather requirements, translate them into actionable data specifications, and ensure alignment with organizational goals.
Develop and deploy data modeling solutions to streamline enterprise information management.
Perform fit-gap analyses and risk assessments of data systems such as SAS, SAP, and IBM, ensuring alignment with business processes and requirements.
Process, cleanse, and validate data for analysis while ensuring its accuracy, quality, and consistency.
Provide input into developing standards, guidelines, and procedures to support data integration and governance.
Monitor the performance and quality of data integration processes and suggest improvements to enhance efficiency.
Support business units in generating self-service reports and dashboards to empower decision-making.
Partner with data architecture teams to design and implement solutions that align with supply chain and product planning capabilities.

Bachelor's degree in a related field such as supply chain, material science, data science, or industrial engineering.
3+ years of relevant experience in data analysis, data governance, or data processes within technology and manufacturing industries.
Master's degree in supply chain management, logistics, or industrial engineering with 2+ years of relevant experience.
Proficiency in data analysis tools such as Excel, SQL, Power BI, and Python, with a strong understanding of techniques like VLOOKUP and pivot tables.
Expertise in system analysis, including comprehension of data flows across source systems, business logic, and downstream systems.
Advanced usage of business intelligence and reporting tools.
Knowledge of Intel's Product Life Cycle (iPLC) and processes like SNOP (Supply, Demand, and Revenue planning) and SNOE (Manufacturing Execution and Capacity Planning).
Familiarity with product architecture and planning BOM for silicon and post-silicon products.
Experience with dependent planning and execution systems such as LRP, SAP, and Atlas.
Skills in influencing teams, problem-solving, and process design, coupled with familiarity with master data management and data quality tools like Informatica.

Data Analyst

Key skills