4+ Years of experience in Data Analysis, report generation, business report process maintenance, data verification, data modeling, data warehousing, data validation, and data mining with large datasets of structured and …
4+ Years of experience in Data Analysis, report generation, business report process maintenance, data verification, data modeling, data warehousing, data validation, and data mining with large datasets of structured and unstructured data. Capable of Text Analytics, generating data visualizations using Python, and creating dashboards using tools such as Tableau, Power BI, and MS Excel. Well-versed in data analysis and visualizing using Python and R packages such as NumPy, Pandas, Matplotlib, SciPy, Seaborn, PyTorch, TensorFlow, Sklearn, Keras, and ggplot2. Proven ability to migrate and manage SQL databases on Azure platforms, including Data Lake, Data Lake Analytics, SQL Database, Data Bricks, and SQL Data Warehouse.
• Develop automated data pipeline architecture, extracting data from various external data sources to create a single data
platform and exporting it to reporting tools like Tableau.
• Improve data accuracy and reduce the data processing time by 40% by optimizing and automating data cleansing, extraction,
and analysis processes.
• Implement continuous integration and continuous delivery (CI/CD) pipelines in Azure DevOps, increasing code deployment
frequency by 30%.
• Execute ETL process in Alteryx to extract data from multiple sources (SQL Server, XML, Excel, CSV) and schedule workflows.
• Establish data models to support advanced analytics and reporting, enabling data-driven decision-making and contributing to
a 25% increase in revenue through improved business insights.
• Industrialize a robust data cleaning and wrangling pipeline, reducing overall processing time by 25%.
Develop automated data pipeline architecture, extracting data from various external data sources to create a single platform and exporting it to reporting tools like Tableau.
Improve data accuracy and reduce the data processing time by 40% by optimizing and automating data cleansing, extraction, and analysis processes.
Implement continuous integration and continuous delivery (CI/CD) pipelines in Azure DevOps, increasing code deployment frequency by 30%.
Execute ETL process in Alteryx to extract data from multiple sources (SQL Server, XML, Excel, CSV) and schedule workflows.
Establish data models to support advanced analytics and reporting, enabling data-driven decision-making and contributing to a 25% increase in revenue through improved business insights.
Industrialize a robust data cleaning and wrangling pipeline, reducing overall processing time by 25%.
Developed Tableau dashboards to track performance metrics, improving team productivity by 10%.
Designed an Extract-Transform-Load process to load 200TB of data into a data warehouse using SQL Server Integration Services (SSIS).
Utilized Google Analytics insights to implement targeted strategies, contributing to a 30% increase in user engagement metrics.
Built and optimized 5 machine learning models in Databricks, achieving a 28% improvement in accuracy compared to traditional methods.
Collaborated with stakeholders to develop and maintain data standards and naming conventions, improving data consistency and facilitating effective data governance practices.
Utilized Azure Databricks and Azure Synapse Analytics for exploratory data analysis, resulting in a 25% reduction in the time required for uncovering in-depth insights and discovering patterns in the data.
Applied advanced analytics techniques to create 24 Power BI dashboards and generate 35 ad hoc reports, enhancing data visibility and analysis.
Monitored the performance of the Snowflake platform and implemented performance tuning strategies, optimizing SQL queries and troubleshooting performance issues, resulting in a 30% improvement in query performance and enhanced user experience.
Designed, developed, and tested QlikView scripts to import data from source systems and test QlikView reports/dashboards to meet customer requirements.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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