Manager, Finance Business Intelligence & Data Products
Job in
Northfield, Cook County, Illinois, USA
Listed on 2026-06-15
Listing for:
Medline Industries
Full Time
position Listed on 2026-06-15
Job specializations:
-
IT/Tech
Data Analyst, Data Science Manager, Business Systems/ Tech Analyst
Job Description & How to Apply Below
Job Summary The Manager, Finance Business Intelligence & Data Products is responsible for delivering business intelligence, visualization, reporting, and analytics solutions for the Finance organization. This role partners cross-functionally to design, develop, and implement governed, reusable data products and dashboards that monitor key performance indicators and drive business decisions. The role combines hands-on technical leadership with people leadership, advancing modern BI practices such as semantic-layer design, KPI governance, and self-service analytics on a cloud data platform, while maintaining strong standards for data quality, lineage, and documentation.
Job Description
Job Responsibilities:
Business Partnership & Solution Delivery Collaborate with Finance leadership and business partners to understand reporting and analytical needs, and translate them into scalable, reusable data products. Lead requirements discovery, KPI definition discussions, and design reviews; convert business intent into clear specifications for facts, dimensions, KPIs, and dashboards. Manage the design and delivery of dashboards and analytics solutions that monitor key performance indicators and drive business decisions.
Serve as a trusted advisor on automation, self-service, and rationalization opportunities across the reporting landscape. BI Platform Development (Microsoft Fabric & Power BI) Design, develop, and maintain analytics content on Microsoft Fabric, including Lakehouse / Warehouse objects, semantic models, and Power BI work spaces. Build and review high-quality Power BI dashboards and paginated reports with strong UX, performant DAX, and clear narrative.
Define and apply platform standards such as workspace structure, deployment pipelines, refresh strategy, row-level security, and naming conventions. Support modernization of legacy BI assets onto Microsoft Fabric and Power BI, including portfolio rationalization, consolidation, and decommissioning of duplicate reports. Semantic Layer, Data Modeling & KPI Governance Design and evolve a semantic layer for Finance: conformed dimensions, transaction-grain and snapshot facts, and business-facing views aligned to how Finance operates.
Develop reusable business logic and calculation patterns (DAX, SQL, and Python) that promote consistency and prevent metric drift across reports. Lead KPI definition, governance, and documentation — including name, formula, grain, source of record, owner, validation rule, and control sensitivity — maintained in a trusted catalogue. Partner with controllership, audit, and risk stakeholders to ensure KPIs supporting close, compliance, and external reporting are accurate and traceable.
Data Engineering, Python & Automation Use Python (pandas, notebooks, and Spark / PySpark where applicable) for data analysis, transformation, reconciliation, and automation of recurring Finance tasks. Drive process improvements by automating manual reporting, controls evidence, and reconciliations through a combination of data pipelines, notebooks, and Power BI. Partner with Data Engineering on layered architecture patterns (e.g., Bronze / Silver / Gold) that ingest data from ERP, operational, and custom source systems.
Promote modern engineering practices within the team: version control, code review, testing, reusable libraries, and CI / CD for data and reporting assets. Data Quality, Lineage & Documentation Establish and uphold data quality, lineage, and documentation standards across Finance data products, with clear source-to-KPI traceability. Implement data quality checks, control rules, and reconciliations between source systems, the semantic layer, and downstream Power BI deliverables.
Maintain documentation that is usable by both technical and business audiences, including data product descriptions, KPI dictionaries, and change history. Foster transparency around known limitations, assumptions, and pending source-system clarifications. Leadership & Team Development Lead and develop a team of BI developers and / or analysts: hiring, coaching, performance management, capacity planning, and career growth. Set the technical bar…
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