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Overview:
This role is responsible for consolidating and analyzing business processes and stakeholder requirements based on inputs of business, translating the business needs into BI features, and contributing to embedding such business features on BI dashboards. The Data & BI Specialist will lead various projects for global business units.
Essential Job Functions & Responsibilities:
Job Specifications/Skills:
1. 6+ years of experience as a BI Specialist working with Microsoft Power BI (Desktop, Service, Gateways) using diverse data sources such as Oracle JDE, along with advanced DAX, M‑code, data modelling, and visualization design.
2. Hands-on expertise across key BI and data engineering tools including Power BI, SQL (advanced querying & optimization), Azure Data Factory (ADF), Python, and ETL/data integration solutions.
3. Strong background in data modelling (star/snowflake, dimensional modelling), cube development, DAX authoring, M‑language scripting, and advanced calculation logic for analytics use cases.
4. Experience in setting up data architecture either on Microsoft Fabric or on Synapse Analytics and working independently on end-to-end solutions.
5. Should have hands-on experience with PySpark, Lakehouse, and Data Warehouse technologies.
6. 2+ years’ experience with the Business Objects BI Platform (BOBJ), covering configuration, security, server administration, migrations, Web Intelligence (Webi), IDT, and BI Launchpad operations.
7. Experience with Microsoft BI Stack (SQL Server, SSIS, SSRS, SSAS) including cube processing, deployment, and performance optimization.
8. Proven ability to translate business requirements into technical specifications, identify data sources, perform complex querying, and build high‑quality dashboards and reports.
9. Experience designing mobile-friendly Power BI dashboards, embedding analytics into web/mobile applications, and implementing row-level security (RLS) and application-layer security models.
10. Strong understanding of database architectures, data lakes, data warehouses, and advanced analytics use cases on Azure or AWS cloud platforms, experience with Microsoft Fabric or similar modern data platforms.
11. Knowledge of CI/CD, DevOps practices, and Git for managing BI and data engineering lifecycle components.
12. Relevant certifications in Azure, AWS, data warehousing, or BI technologies are a strong advantage.
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