Rayane Szczepanowski

• - Implementation of the medallion architecture

• - Implementation of Unity Catalog

• - Cluster cost optimization

• - Provision of detailed reports on the IT infrastructure status (printers, PCs, virtual machines, etc.).

• - Monitoring, analysis, and synthesis of park-related data to optimize maintenance and asset management.

• - Automation of data collection and processing to provide reliable and up-to-date dashboards.

• - Optimization of scheduling, reducing costs and processing times by 4 hours.

Migration of an On-Premise architecture to Cloud:

• - Migration of SSIS flows to Azure Data Factory (ADF)

• - Development of pipelines in Azure Data Factory, depositing data in Parquet format in Azure Blob Storage.

• - Implementation of a medallion Delta Lake architecture (Bronze, Silver, Gold, Platinum) for data management and transformation.

• - Development of Databricks Notebooks to load and transform data between the different layers of the Datalake.

• - Monitoring of double RUNs (parallel executions) pending the decommissioning of the old On-Premise architecture.

• - Creation of reports on Power BI

• - Development of SSIS flows with CDATA connectors (API)

• - POC of existing uses on Microsoft Fabric and Databricks

Technical Stack: SQL Server, SSIS, Power BI, Databricks, Azure Data Factory (ADF), Azure Blob Storage, Parquet, CDATA Connectors, Python, Azure.

Migration of an On-Premise architecture to Cloud:

- Migration of SSIS flows to Azure Data Factory (ADF)

- Development of pipelines in Azure Data Factory, depositing data in Parquet format in Azure Blob Storage.

- Implementation of a medallion Delta Lake architecture (Bronze, Silver, Gold, Platinum) for data management and transformation.

- Development of Databricks Notebooks to load and transform data between the different layers of the Datalake.

- Monitoring of double RUNs (parallel executions) pending the decommissioning of the old On-Premise architecture.

- Creation of reports on Power BI

- Development of SSIS flows with CDATA connectors (API)

- POC of existing uses on Microsoft Fabric and Databricks

Technical Stack: SQL Server, SSIS, Power BI, Databricks, Azure Data Factory (ADF), Azure Blob Storage, Parquet, CDATA Connectors, Python, Azure.

• • Coaching the team to improve their skills on the MSBI suite

• • Development of a system architecture (active/active) based on GTM and Load Balancing to host the Power BI report, allowing access for 5000 users. This solution was designed to anticipate any potential failure.

• • Design of a Power BI Dashboard providing an overview of different communication parks, such as mobile, voice, and data, enabling analysis of consumption, billing, revenue, and park details.

• • Design of a monitoring dashboard to track report usage.

• • Design of tabular cubes and development of reports in Power BI.

• • Integration of ODBC connection to import data from HIVE via SSIS.

• • Development and automation of data loading flows (SSIS)

• • Optimization of SQL processes and existing data loading flows.

• • Incremental data integration with automated partition management on SQL Server.

• • Optimization of cube processing (incremental) and automated partition management.

• • Gathering business requirements.

• • Testing/Production deployment.