Amine Salmi

– Designed and maintained scalable ETL pipelines using Python, SQL, and Azure Data Factory, processing large-scale datasets across multiple sources. – Automated data transformations and optimized workflows, improving pipeline reliability and reducing manual intervention. – Used Azure Data Lake and Databricks to process data and prepare it for analysis. – Integrated structured and unstructured data from APIs, databases into centralized data platforms. – Built Power BI dashboards to monitor operational KPIs and system performance, improving visibility for business partners. – Applied data quality checks and monitoring processes to ensure consistency and reliability of data pipelines.

– Developed ETL pipelines using Python, Databricks, and Talend to ingest and transform structured and unstructured datasets. – Designed and implemented relational data models support scalable reporting, and analytics use cases in Power BI and Tableau. – Collaborated with R&D teams to translate business requirements into robust data solutions. – Contributed to the deployment of machine learning workflows on Azure. – Optimized SQL queries and data transformations to improve performance of reporting systems.

– Built ETL pipelines to ingest and transform credit risk data from multiple sources. – Developed Airflow workflows to automate data processing and model evaluation pipelines. – Prepared and validated datasets for machine learning models using SQL and Python. – Built datasets and evaluation pipelines for machine learning models. – Provided insights to business teams through data analysis and reporting tools.

– Conducted HR data analysis to support strategic workforce planning. – Designed dashboards and KPIs for executive reporting. – Built dashboards and reports using Qlik Sense/QlikView for executive decision-making. – Applied statistical methods to classify and analyze workforce data. – Developed decision-support tools to improve HR strategy.