Business Intelligence Specialist

Business Intelligence Specialist

RESPONSIBILITIES

• 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 appl