Manager Business Intelligence - Hybrid

About the role

The Manager, Business Intelligence owns the day-to-day delivery of business intelligence, reporting, and analytics work across the BI/AI function. This role acts as a primary liaison between the business community and the onshore and offshore development teams.

Responsibilities

• Build expert knowledge of Klein Tools business applications and maintain frequent contact with stakeholders.
• Gather and document business requirements, define the scope of each request (outputs, data sources, acceptance criteria), and hand off clear, unambiguous specifications to the development team.
• Direct and coordinate day-to-day work across the onshore and offshore BI team; assign tasks, set and manage priorities, remove blockers, and ensure on-time delivery against agreed timelines.
• Coordinate delivery of AI agent and AI-enabled analytics initiatives - scoping requirements, tracking progress, and aligning the team with the function’s AI roadmap and the Agentic Register.
• Maintain the BI backlog and delivery pipeline; track and report on progress, throughput, and team capacity, and drive backlog burn-down as request volume grows.
• Oversee the creation and maintenance of application, user, and training documentation for BI and analytics solutions, and support user enablement.
• Coordinate and communicate BI application releases and system upgrades, including aligning data warehouse activities during upgrades of other IT systems.
• Monitor delivery quality and routine data loads in partnership with the team; escalate issues to the Director and ensure timely resolution.
• Support source-system analysis and data-profiling efforts by coordinating the team and clarifying business rules and data issues with stakeholders.
• Identify needs and opportunities for improved data management and delivery, and recommend them to the Director for prioritization.
• Maintain strong relationships with business users and act as their advocate within IT, managing expectations across competing demands.

Requirements & scope

This is a delivery, coordination, and people-leadership role that translates direction into clear, actionable work, keeps delivery moving, and ensures quality and timeliness. Strong communication and the ability to discuss solutions with both technical and business audiences are central to the role, as is a working command of the BI and AI toolset the team operates.

Qualifications

• Education: Bachelor’s degree in Information Systems, Computer Science, Business, or a related field - or equivalent practical experience.
• Experience: 8+ years in business intelligence, reporting, or data-delivery roles, with 2+ years coordinating or leading projects, teams, or vendors.
• Required Knowledge & Skills: Exceptional written and verbal skills; comfortable eliciting requirements directly from business users and translating between business and technical audiences. Solid working understanding of SQL, data warehousing concepts, ETL, reporting, and OLAP cubes - enough to scope work, brief developers, and validate deliverables.
• Required Technical Knowledge: Working familiarity across the team’s stack - enough to scope and estimate requests, brief and direct developers, review deliverables, and speak credibly with users and the team: Data integration & ETL - SQL Server Integration Services (SSIS) and modern pipeline patterns (e.g., Azure Data Factory, Fabric pipelines). Reporting & analytics - Power BI (reports, dashboards, datasets, data-model basics) and SQL Server Reporting Services (SSRS) for paginated/operational reporting. Modeling - SQL Server Analysis Services (SSAS) tabular models and OLAP cubes. Data platform - SQL Server (read and follow SQL, schema conventions), Microsoft Fabric (lakehouse/warehouse and Power BI integration concepts), and relevant Azure services (storage, data, identity).

Preferred (a Plus)

• Ai agents - familiarity with AI agent concepts and agentic patterns (e.g., retrieval-augmented generation, tool/API use, LLM APIs), and the ability to scope and coordinate AI agent delivery alongside traditional BI work.
• Ai coding assistants - exposure to AI coding assistants (e.g., GitHub Copilot, Claude Code) and how they accelerate development, testing, and documentation.
• Hands-on depth - prior practical experience in any part of the stack above (e.g., authoring Power BI reports, writing SQL, or building AI agents) beyond a functional understanding.
• Domain - exposure to data from ERP / order-management / supply-chain systems in a manufacturing or distribution business.
• Machine learning & predictive analytics - familiarity with ML concepts and predictive modeling in a business context, particularly exposure to use cases such as sales forecasting or sentiment analysis; ability to coordinate delivery of ML-driven solutions alongside traditional BI work, including engaging with data scientists or model developers and translating outputs into actionable dashboards and reports.
• Tooling & certifications - experience with ticketing / work-tracking systems, standard PM practices, and relevant Microsoft data, AI, or project certifications.