Motivated and analytical Data Analyst with 3+ years of experience in data, visualization, and reporting. Strong skills in data acquisition, cleaning, manipulation, and analysis using SQL, Python, and Excel. Built reports…
Motivated and analytical Data Analyst with 3+ years of experience in data, visualization, and reporting. Strong skills in data acquisition, cleaning, manipulation, and analysis using SQL, Python, and Excel. Built reports, visualizations, and dashboards using Tableau, and Quick sight. Extensive experience in Text Analytics, generating data visualizations using R, Python and creating dashboards using tools like Tableau. Excellent communication skills with experience presenting findings to both technical and non-technical audiences.
Developed and maintained AWS Glue pipelines and write Data transformation and data wrangling scripts using Python.
Create Views, stored procedures and write complex SQL queries as per the requirements.
Design and evolve the data model & infrastructure for better query performance.
Create Dashboards and sub-reports in Quick Sight for different departments.
Communicate frequently with different divisions of the company to understand data enhancement needs and find opportunities to automate procedures.
Prepared detailed insights for upper management on various Vendor's performance and provided statistical measures to analyze their relationships and determine which vendors to buy out (As part of the analysis, I built and included the results of numerous forecasting and regression models.)
Managed and developed ETL pipelines, created Data catalogs, data preparation/integration & data modeling.
Assisted senior analysts with data collection, cleaning, and analysis.
Built dashboards to monitor server activity, data flow, usage statistics related to organizational people data for leadership to identify performance issues/enhancements effectively.
Implemented the number of customer clustering models and these clusters are plotted visually using Tableau legends for the higher management. Analyzed large datasets from various sources (e.g., CRM, website analytics, market research) to identify trends, patterns, and key performance indicators (KPIs).
Developed and maintained AWS Glue pipelines.
Wrote data transformation and data wrangling scripts using Python.
Created views, stored procedures, and complex SQL queries as per requirements.
Designed and evolved the data model and infrastructure for better query performance.
Created dashboards and sub-reports in Quick Sight for different departments.
Communicated frequently with different divisions of the company to understand data enhancement needs and find opportunities to automate procedures.
Prepared detailed insights for upper management on vendor performance.
Provided statistical measures to analyze vendor relationships and determine which vendors to buy out.
Built and included the results of numerous forecasting and regression models as part of the analysis.
Managed and developed ETL pipelines.
Created data catalogs, data preparation/integration, and data modeling.
Assisted senior analysts with data collection, cleaning, and analysis.
Built dashboards to monitor server activity, data flow, and usage statistics related to organizational people data for leadership.
Implemented customer clustering models and plotted the clusters visually using Tableau legends for higher management.
Analyzed large datasets from CRM, website analytics, and market research to identify trends, patterns, and KPIs.
Leveraged SQL and Python to extract, clean, and transform data from various sources for analysis.
Performed data analysis using statistical methods and machine learning to identify trends, patterns, and key insights.
Developed and maintained interactive dashboards and reports using Tableau to communicate data insights effectively to stakeholders.
Supported stakeholders across departments by providing data-driven recommendations and reports to improve decision-making.
Created views, stored procedures, and user defined functions and optimized large queries.
Supported business decision-making by providing data-driven recommendations to improve.
Managed AWS Glue pipelines and integrated with other AWS services.
Designed, built, tested, and maintained data pipelines, data integration, ETL processes, and data management delivery within an S3 global data lake and Redshift environment using AWS Glue Jobs, Triggers, and Workflows.
Built strong relationships with data scientists, administration, stakeholders, and customers to provide weekly presentations, KPI reporting, and dashboards.
Created and maintained databases using data from primary and secondary sources, as well as scripts to make the data review process more flexible and scalable across data sets.
Pulled, organized, and analyzed relevant data from multiple sources using SQL and Python.
Designed, built, and launched data pipelines to build the next generation of data tools that generate business insights.
Built dashboards and data infrastructure towards a coherent tech and data ecosystem.
Wrote and deployed SQL to archive or purge data from databases and to locate, review, explain, and document data for retention requirements.
Resolved deduplication, canonicalization, and record-linkage by performing entity resolution on a procurement dataset using AWS Glue.
Corrected mapping issues and errors throughout the dataflow.
Prepared final analysis reports for stakeholders to understand the data-analysis steps and take important decisions based on various facts and trends.
Worked with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
