Business Intelligence Manager

About the role

The Business Intelligence Manager will lead multiple BI initiatives from concept to production, ensuring robust data pipelines, high‑quality reporting, and strong partnership with business stakeholders across a global organization.

Key responsibilities

• Lead end‑to‑end BI projects, managing scope, milestones, risks, dependencies, intake, prioritisation, backlog grooming and sprint/release planning.
• Design, build and maintain scalable ELT/ETL pipelines using Azure Databricks and architect solutions across Azure Data Factory, Synapse Analytics, ADLS Gen2 and Azure DevOps CI/CD.
• Create Power BI semantic models, reports and dashboards; define standards for DAX, data models, UX, row‑level security, deployment pipelines, workspace governance and licensing.
• Develop Python‑based transformations, automation workflows, data‑quality frameworks, reconciliation and pipeline testing while promoting Git, code review, unit testing and documentation.
• Collaborate directly with business stakeholders to gather and challenge requirements, translate needs into structured delivery roadmaps and communicate status, risks and decisions in both Japanese and English.
• Define and enforce BI technical standards, testing strategy, UAT coordination, support model, incident triage, SLA definitions and on‑call processes.

Required profile

• Master’s degree in Computer Science, IT, Business/Data Analytics or a related field.
• Business‑level proficiency in English for technical discussions, documentation and workshops.
• Proven hands‑on experience with Azure services (Databricks, Data Factory, Synapse, ADLS Gen2, DevOps).
• Advanced Power BI expertise (DAX, Power Query, semantic modelling, deployment pipelines, RLS, Fabric/Premium).
• Strong Python programming skills for data transformation and automation.
• Deep knowledge of SQL, data warehousing, dimensional modelling, medallion/data‑vault architecture and performance optimisation.
• Ability to manage multiple priorities and stakeholders in a complex global organisation.
• Excellent communication, mentoring and code‑review capabilities.

Required skills

• Azure Databricks
• Azure Data Factory
• Azure Synapse Analytics
• Azure Data Lake Storage Gen2
• Azure DevOps CI/CD
• Power BI (DAX, Power Query, semantic modelling, deployment pipelines, RLS)
• Microsoft Fabric (OneLake, Lakehouse, Real‑Time Analytics)
• Python
• SQL
• Data warehousing and dimensional modelling
• Medallion and data‑vault architecture
• Performance optimisation
• Git, unit testing and documentation
• Infrastructure‑as‑code (Terraform, Bicep)
• dbt or similar analytics‑engineering framework (optional)