Freelancer profile translated to English.
Back to original languageAbout Bennet
Data pipelines, Data Warehousing and Reporting in the Microsoft Data Stack – from the integration of heterogeneous data sources to the productive Power BI dashboard.
Focus:
- ETL/ELT: Data pipelines with SQL Server and Azure Data Factory for data from databases, APIs, ERP systems, cloud sources, and flat files.
- Data Warehousing: Data warehouses and dimensional data models on SQL Server.
- Reporting: Power BI dashboards and reporting solutions with Power Query & DAX.
Tech Stack:
SQL Server · T-SQL · Power BI · Azure Data Factory · DAX · Python · Azure DevOps · Git
100% remote | Availability in CET
German
Native or bilingual
English
Fluent
Remote only
Primarily works remotely
Experience
- Eigenprojekt - https://github.com/BGurklies/olist-ecommerce-dwhE-Commerce Data WarehouseMarch 2026 - Today (3 months)
- In-house development of a production-ready Data Warehouse on MS SQL Server – central data store for structured, quality-assured consolidation of all company data ready for analysis.
- Three-tier architecture (Raw / Cleansed / Mart) with batch historization, incremental loading concept (MERGE + SHA2-256 Row-Hash Change Detection), data quality checks, and complete audit trail.
- Metadata-driven orchestration via a central configuration table with automated scheduling via SQL Server Agent.
- Kimball Star Schema in the Mart as the basis for a multi-page Power BI dashboard for sales, operations, and customer KPIs.
- Garbe IndustrialReal Estate Budget Reporting AutomationREAL ESTATEJune 2025 - September 2025 (3 months)Hamburg, Germany
- Full automation of previously manual ERP budget reporting — merging, cleaning, and preparation of all raw data from heterogeneous source systems into an SQL-based data flow on MS SQL Server.
- Automated monthly scheduling via SQL Server Agent — finished report is provided directly to business departments; manual preparation steps completely eliminated, enabling historical data analysis.
- Garbe IndustrialData EngineerREAL ESTATEMarch 2025 - November 2025 (8 months)Hamburg, Germany
- Development and enhancement of automated data pipelines for integrating real estate and financial data from heterogeneous source systems (databases, cloud storages, APIs, ERP, flat files) into the central Data Warehouse based on MS SQL Server – replacement of manual data preparation processes with automated, quality-assured data flow via the DWH.
- Migration of existing SSIS pipelines to native Stored Procedures – consolidation of ETL logic at the database level for better maintainability and performance through indexing and incremental loading processes.
- Design and implementation of Power BI dashboards for portfolio management reporting in real estate fund management – business departments receive current analyses fully automatically without manual pre-work on source data.
- CI/CD for DWH components with Azure DevOps — standardized, versioned deployments in test and production environments.
- Development of an MCP server for AI-supported database queries on Oracle and SQL Server – enables natural language data analysis in the development environment.
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Education
- Bachelor of Science Computer Science / Software EngineeringTechnische Hochschule Lübeck2025Schwerpunkte: Data Engineering, Data Analytics, Softwareentwicklung, Machine Learning. Abschlussnote: 1,9 | Thesis-Note: 1,0. Bachelor-Thesis: "Entwicklung und Optimierung eines hybriden Deep Learning Modells zur Erkennung und Klassifikation von Krebs in Blasen- und Nierengewebe in Zystoskopie-Bildern". Tools: Python · PyTorch · CNN · GAN · Transfer Learning.
Certifications
- Google Advanced Data Analytics Professional CertificateCoursera2024