Business Intelligence Specialist

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Skills you'll use

What you'll do

• Supply Chain Knowledge & Business Acumen
• Act as a trusted, knowledgeable resource for supply chain stakeholders, supporting discovery sessions across manufacturing sites to understand processes, pain points, and data availability.
• Apply knowledge of SIOP/S&OP, MRP, demand planning, capacity planning, and inventory management to support the translation of business concepts into analytics requirements and data models under the direction of the Analytics Manager.
• Validate data outputs against operational reality; identify data quality issues rooted in business process gaps.
• Contribute to and help maintain business glossaries, KPI definitions, and domain context documentation for the ISC Analytics portfolio.
• Business Analysis & Applied Statistics
• Conduct exploratory data analysis to identify trends, anomalies, and opportunities across supply chain datasets.
• Apply basic statistical methods (descriptive statistics, correlation, regression, time-series decomposition) to support forecasting and root cause analysis.
• Design, build, and maintain interactive dashboards and scorecards in Power BI per stakeholder requirements.
• Analytics Development & Data Pipeline Support

Who can apply

• Bachelor’s degree in Supply Chain Management, Operations Management, Industrial Engineering, Data Analytics, or a related field.
• 3+ years of experience in a supply chain analytics or business intelligence role within a manufacturing or industrial environment.
• Demonstrated understanding of supply chain processes: S&OP/SIOP, MRP/ROP, demand/capacity planning, inventory management, or production scheduling.
• 2+ years of hands-on experience with Databricks or a comparable cloud data platform (Snowflake, BigQuery, Synapse).
• Proficiency in Python and SQL for data manipulation, pipeline development, and analytical scripting.
• Experience building dashboards and reports in Power BI or an equivalent tool (Tableau, Looker, etc).
• Familiarity with medallion architecture patterns and data lakehouse concepts.
• Working knowledge of ETL/ELT pipeline development and data quality management.
• Experience with workflow automation tools (Power Automate, Databricks Workflows, Apache Airflow, or similar).
• Strong proficiency in Microsoft Excel for ad hoc analysis, data validation, and stakeholder communication.

About Xylem

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