Wagdy El-Sherbiny

ADNOC Distribution is the UAE's leading operator of retail fuel service stations. ADNOC Wallet makes ADNOC service station payments quick and easy. It's fully secure and keeps track of everyday spending at ADNOC service stations. It includes refueling, shopping, lube change, and car washes. In addition, customers can register multiple cars or beneficiaries to an account.

I was the software engineer who participated in and developed all objects related to the data area, including databases such as triggers, stored procedures, jobs, data warehouse, pipelines, and reporting. I created a set of systems, including the following:

• A card management system (CMS).
• A comprehensive centralized software solution providing our clients with a user-friendly interface that integrates tightly with other back-end and external systems, such as customer management, beneficiary management, token management, transaction management, system settings, BI reports and dashboards, differential pricing, notification management, ERP integration, loyalty system, e-vouchers, coupons, data migration, and card printing system that personalizes smart cards, vehicle depot system, and invoicing.

Emarat is a multi-channel power and energy company with a network of service stations and fuel depots across Dubai and the Northern Emirates. In this project, I worked on the following:

• Implementing and customizing a turnkey solution to meet the company's station management and retail services needs.
• Participating in the system requirement gathering and analysis phases.
• Analyzing and compiling components needed for data migration and integration with various systems, such as Oracle ERP, NCR, and NAMOS.
• Developing a data migration workflow to move data into a new system using SSIS.
• Building a differential pricing system and NCR discounts.
• Developing various reports and dashboards using SSRS and Power BI.

I collaborated with a team to design and implement a set of reports and dashboards for executives and operation users of Kuwait’s Ministry of the Interior e-passport system. I performed requirements analysis, made system designs, oversaw implementation, and drafted documentation. Also, I created numerous processes using Microsoft BI tools to develop and implement a data warehouse and designed an SSIS package that extracts citizen data from an SQL Server database using lookup transformation and the Foreach Loop container. Finally, I built dashboards to demonstrate the overall performance of the passport printing center.

The Kuwait National Petroleum Company (KNPC) is Kuwait's national oil refining company. As a software engineer, I participated in building a turnkey solution for retail service stations from scratch to meet KNPC's business needs and operations. I participated in all of the systems development lifecycle (SDLC) to build a centralized solution that manages customers' profiles, consumption, transactions, invoicing, loyalty points, e-vouchers, pre-printed vouchers, and data integrations with Oracle ERP and NCR systems, in addition to building modules related to managing users permissions and system setting and data backup routines.

I worked on the first Digital Oil Field (DOF) project in Kuwait, using Petroleum Experts (PETEX) technology to enhance the oil well production and operations by providing frameworks and dashboards for decision-makers. I served as the first line of support for the PETEX solution, assisting petroleum engineers during daily operations, overseeing troubleshooting data issues, and helping users interpret and understand report data. I used the following software solutions: Integrated Visualisation Management (IVM), Integrated Production Modeling (IPM), IFM, PROSPER, and Model Catalogue.

This web application manages all the Kuwait National Guard's vehicles fleet operations. As a software engineer, I oversaw gathering requirements, analyzing the client's needs, and providing detailed design documents to the team. I worked closely with the development team to design and implement the database's objects and the Windows Communication Foundation (WCF) service to provide the front-end developers with the required info for a web app. Also, I managed the production deployment activities and troubleshooting issues and conducted training and user acceptance testing (UAT) sessions for end-users.

The Ford GoBike System dataset contains information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. There are approximately 183,400 records with attributes in the dataset that describe rides, including start station, end station, and duration.

I illustrated the steps and procedures used for wrangling a real-world dataset known as WeRateDogs. WeRateDogs is a humorous Twitter account that rates dogs with commentary. I collected data from different resources, such as ZIP and CSV files, and queried the Twitter API to fetch data.

Built a real-time data pipeline that monitors three trading symbols' order trades and extracts data as of the ACT messages protocol. The script extracts and parses data and then loads it into the Oracle database.

• Participated in PySpark script development, converting legacy reports into new ones that optimized execution time and processed the vast amount of daily data, 500+ million transactions.
• Developed a regression testing program that validates the outcomes of one of the leading trading solutions at SIG. That application was handy for top management to validate the data outcome.

• Developed an ETL, where parsing XML files loads data into an Oracle database table. The pipeline automatically parses any newly added XML tags into the DB.
• Developed an interactive dashboard using Qlik Sense after creating a data model suited for reporting.

Converted a legacy Perl program into Python. The scripts aim to process trading orders and calculate the five-minute sliding average for each symbol.
The program steams the data from Fido API, then aggregates data by calculating the one-minute average, then calculates a five-minute average and stores the result in the Oracle DB table.

Implemented a Python program to replace a legacy system, drastically reducing processing time for calculating trading volumes per symbol and exchange messages. Reduced processing duration from 7 to 10 hours to approximately 20 to 30 minutes.

Designed and developed a robust database logging and debugging utility for streamlined troubleshooting. Also, created a Python module for easy integration into scripts, bolstering debugging capabilities.

• Engineered a Python script to extract data from URLs, parse JSON information, and seamlessly store it within an SQL server database for efficient data management.
• Created a shell script designed to retrieve data from the FIDO trading system. - Implemented filtering to extract essential information, saving it into a CSV file. - Utilized external tables to facilitate the loading of data into Oracle tables.