BI Analyst

Role Overview The BI Analyst plays a key role in supporting Supply Chain Operations by creating or managing data sets, building tools that enable collecting, validating, and organizing data, developing reports and dashboards that lead to insights and automations that drive user efficiency. This position works closely with Supply Chain Analytics, Global Manufacturing Ops, Solution Design Management Team, VSIT, to support the creation of reporting and analytics.

The BI Analyst is responsible for transforming raw operational data into analytics and actionable insights. They develop reliable datasets and metrics, analyze datasets, to support informed production and sourcing decision-making. The role requires maintaining data quality, following established processes, identifying and resolving issues. The role will also be responsible for building lightweight applications that improve internal workflows and reduce manual effort.

Core Responsibilities (Day-to-Day)

- Analytics & Reporting: Develop supply chain reports and dashboards using tools such as SQL, Snowflake, MicroStrategy, and Sigma. Track business-defined KPIs and ensure timely, accurate reporting for production and sourcing teams.
- Dashboard Maintenance & Monitoring: Maintain and enhance reporting assets based on business feedback. Automate recurring reports and proactively identify anomalies or data inconsistencies.
- Data Engineering & ETL: Develop and optimize SQL queries to extract, transform, and structure data from internal and external data sources, enabling effective analytics.
- Data Management & Validation: Collect, clean, and validate data from Enterprise Systems (e.g., SAP/Centric/Salesforce) and other sources.
- Domain Expertise: Be the go-to person for the tools and data they support, including understanding the usage, the business processes it supports
- Enterprise Integration Support: Assist integrating data across Enterprise Systems to ensure seamless data flow, improved visibility, and consistency across business functions.




- Business Application Development: Leverage low-code tools such as Sigma, Salesforce, Power Automate and Python to build lightweight applications that improve internal workflows and reduce manual effort.
- Cross-functional Collaboration: Work closely with production, planning, and sourcing teams to ensure KPIs are aligned, tracked effectively.

Skills & Qualifications

- Education: Bachelor’s degree in Computer Science, Information Systems, Supply Chain, Analytics, or related fields.
- Experience: 2-3 years of experience in Business Intelligence, Data Analytics, or Supply Chain Analytics (internships or project experience considered).
- Technical Skills:
- Proficient in SQL, with experience writing complex queries, optimizing performance, and managing relational databases.
- Proficiency in Excel (Power Query, Pivot Tables, VLOOKUP/XLOOKUP, basic formulas).
- Experience in BI/visualization tools such as MicroStrategy, Power BI, Tableau, or Sigma.
- Basic understanding of Data Warehousing concepts and tools such as Snowflake (or similar platforms like DataBricks/Hadoop).
- Exposure to Python (Pandas, basic scripting) for data handling (extract, transform and loading).
- Experience with low-code/no-code tools like Sigma, Streamlit, or Power Apps.
- Familiarity with data cleaning and validation techniques.
- Experience working with large raw data sets and data ETL development including the design and maintenance of data extract, transform and load processes to streamline data collection and management.
- Attention to detail with a focus on data hygiene and documentation including writing clear specs,



data dictionaries and pipeline diagrams.
- Computer Science Fundamentals:
- Understanding of programming fundamentals, object-oriented programming, and algorithms.
- Ability to apply data modeling principles and relational database theory & normalization techniques.
- Understanding of data structures and appropriate usage (arrays, lists, dictionaries, trees).
- Analytical Skills:
- Ability to work with large datasets to identify trends, patterns, and anomalies.
- Strong attention to detail with a focus on data accuracy and quality.
- Basic understanding of KPIs and metrics, preferably in a supply chain or operations context.
- Ability to answer business problems and present findings to stakeholders leveraging appropriate visualization techniques
- Business & Functional Understanding:
- Knowledge of supply chain processes (product development, sourcing, procurement, production, inventory, logistics) is preferred.
- Understanding of ERP systems such as SAP or similar platforms is an advantage.
- Soft Skills:
- Good problem-solving and logical thinking ability.
- Robust communication skills to collaborate with cross-functional teams.
- Ability to manage tasks independently and follow structured processes (SOP-driven environment)
- Willingness to learn and adapt in a fast-paced, data-driven environment.
- Nice to Have / Additional Skills
- Knowledge of apparel/retail supply chain or manufacturing domain.
- Internship or academic project involving dashboard creation or data analysis.
- Ability to leverage Robotic Process Automation (RPA) and Agentic AI for development and as part of tool creation.
- Understanding of how AI agents integrate with data ecosystems, such as connecting to SQL warehouses, APIs, or analytics tools to retrieve, transform, or explain data.
- Experience using AI copilots or agents (e.g., Microsoft Copilot, OpenAI-based agents, workspace automation tools) to streamline analysis, documentation, or workflow orchestration.

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