Freelancer profile translated to English.
Back to original languageAbout Karim
I am a senior consultant in Data & Business Intelligence, specializing in the design, optimization, and governance of Power BI and SQL Server solutions. With over 12 years of experience in data, I have supported major groups (industry, health, retail, finance) in building robust data models, strategic dashboards, and high-value-added automation processes.
Key Expertise:
• Power BI (DAX/M modeling, RLS, performance, governance, CI/CD via pbi-tools and GitHub)
• SQL Server, SSIS, Tabular Editor, Azure Data Factory, Fabric
• Multidimensional modeling & SSAS cubes
• Data architecture, ETL automation (PowerShell, Excel VBA, API)
• CRM integration (Salesforce, Factorial, X3, Sylob)
• Deployment and maintenance of financial, sales & supply chain reports
My approach combines strategic vision and technical excellence to transform data into operational decisions and performance levers. I am involved in both dashboard design and the implementation of complete BI environments (Dev/Test/Prod, automation, monitoring).
Keywords: Power BI, SQL, SSIS, Tabular Editor, Azure, CI/CD, Data Modeling, ETL, Reporting, KPI, Dashboard, DAX, Fabric, Business Intelligence, Data Architecture, Data Strategy.
French
Native or bilingual
English
Native or bilingual
Can work on-site
Paris (up to 50km)
Experience
- ODDO-BHF — FinanceData ArchitectJanuary 2026 - Today (7 months)Stack: Microsoft Fabric (Lakehouse, Pipelines, Dataflows Gen2, Direct Lake), Power BI, Snowflake, dbt, Azure, GitHub CI/CD• • Designed the target Lakehouse architecture on Microsoft Fabric (Bronze / Silver / Gold) feeding regulatory, risk and asset-management reporting.• • Industrialized 30+ ingestion pipelines (Pipelines + Dataflows Gen2) with incremental refresh, replacing legacy ETL chains and cuting refresh times by 60%.• • Modeled semantic layers in Direct Lake mode delivering near real-time KPIs to Front-Office and Finance users — millisecond query latency on multi-billion-row fact tables.• • Set up GitHub CI/CD for Fabric items (notebooks, pipelines, semantic models) with environment promotion (DEV → REC → PROD) and automated quality gates.• • Defined data governance standards: naming conventions, lineage, sensitivity labels, row-level security on confidential portfolio data.• • Coached data engineers and BI developers on Fabric, dbt and Power BI best practices; led architecture review board sessions.
- LUMIBIRD GROUPHead of Data & BIOctober 2023 - Today (2 years and 10 months)• Developed and executed a BI roadmap aligned with business objectives.• Manage Business intelligence report and systems for 10 different countries.• Led a team in designing Power BI dashboards to provide actionable insights across Finance, Sales, and Operations.• Managed gross margin analysis, KPI tracking, and financial reporting, optimizing data efficiency.• Collaborated with cross-functional teams to improve data consistency and system integration.• Delivered enhanced data visualization tools to support strategic decision-making.
- GLOBE GROUPEData Consultant / Power BIJuly 2024 - July 2024Paris, FranceTasks performed and problems encounteredSales evolution:Insert a percentage change between each week: done, ok.Calculate a percentage change between non-consecutive weeks (e.g., between W24 and W27): done but requires calculating 6 measures first.Obtain the overall percentage change by family and by product: done for families.Create a table for sales in volume and value with the ability to drill down to product family and product, including a percentage change: ready to use.Sell-out result vs. target in revenue:Create a table with a store column, a result column, a target column, and a % sales vs target column: done assuming the result corresponds to revenue.Overall targets for stores, without distinction between product families: ok.Product stockout:Create a similar table with a store column, a result column, a target column, and a % sales vs target column: ok.Overall targets for stores, without distinction between product families: ok.Correlation of Sell-out, Stock, and DN data:Produce a graph and a table with store entry key, with a granularity of sales evolution, including Stock and DN data: understanding problem, especially for the "supplying" part.Have this data globally by product family and by product.Example of desired graph: allow filtering by product family (Wash, Cold, Oven) and add filters at the store level.Page with visualization of tables:Create a page with the same visualization of the two tables mentioned above: in progress.Attendance rate:
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Education
- Master in Business IntelligenceUniversity of Lorraine2013
- Master's degree in Information Systems Audit & Management ControlSKEMA Business School2015
Certifications
- Power BIMicrosoft2019
- Implementing Data WarehouseMicrosoft2018