Business Intelligence Specialist

Xylem is a Fortune 500 global water solutions company dedicated to advancing sustainable impact and empowering the people who make water work every day. As a leading water technology company with 23,000 employees operating in over 150 countries, Xylem is at the forefront of addressing the world's most critical water challenges. We invite passionate individuals to join our team, dedicated to exceeding customer expectations through innovative and sustainable solutions.

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 Develop and support ETL/ELT pipelines in Databricks using Python/SQL, in coordination with Central IT, to ingest, transform, and serve data from enterprise sources. Configure and maintain schemas, tables, and views within Databricks following medallion architecture (Bronze/Silver/Gold) standards, including curation of the Gold semantic layer that serves dashboards and AI systems. Write performant SQL and Python for data transformation, validation, and pipeline orchestration. Support data quality checks, logging, and monitoring across pipeline layers. Automation & AI Enablement Assess process and workflow needs to determine when an AI-based solution adds value versus when a deterministic automation (e.g., scripted pipeline, scheduled job, rule-based logic) is the more appropriate and reliable approach. Implement and maintain workflow automations using tools such as Power Automate, Databricks Workflows, or similar platforms to reduce manual effort in recurring data processes. Stay current on emerging AI and automation tooling and identify practical applications that align with team priorities. Project Delivery & Team Operations Operate within the team’s hybrid agile/traditional project management framework, including sprint-based delivery cycles, backlog management, and adherence to project timelines, dependencies, and milestone commitments.

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,