CV

📌 Experience

Lead Data Engineer

• Led a dynamic team to drive the development of modularized, automated data engineering pipelines, fostering a culture of excellence and innovation.

• Architected and delivered modularized, automated, event-driven data engineering pipelines and data modeling approaches to ensure scalability and efficiency.

• Managed data updates, imports, exports, segments, and audiences within analytical systems to optimize insights database and marketing automation platform performance.

• Implemented modern code development strategies in collaboration with Data Governance to enhance data quality and streamline the resolution of data issues.

• Monitored and maintained existing data integrations, contributing to the creation of operational procedures and high-level designs for data pipelines and models.

• Collaborated with third-party partners and software providers to enhance or implement new data solutions and processes.

• Acted as the gatekeeper for customer data, ensuring compliance with data privacy standards in collaboration with Data Governance.

• Leveraged Medallion Architecture principles to design and deploy scalable, resilient data solutions.

✨Project

Technologies Utilized:

Cloud Platform: GCP

Languages: Python,Java and SQL

Data Processing: GCP Dataflow, Apache Beam, Apache Spark, Apache Airflow, Dataproc

Data Streaming : Cloud Pub/Sub, Apache Kafka

Data Integration: Cloud Data Fusion, Cloud Functions , GCP Dataflow , Altrex

Data Storage: BigQuery, Snowflake, GCP Cloud Storage

Database: Firestore, Datastore, AlloyDB, Memorystore, BigTable ,Cloud SQL,Redis

Time Series Database: InfluxDB, TimescaleDB

Metadata Management: Apache Atlas, Data Catalog

Infrastructure as Code: Terraform

Security: Cloud IAM, Cloud Security Command Center

CI/CD: GitHub, Cloud Build

Graph Database: Neo4j

Search Engine: Elasticsearch

Containerization: Docker

Container Orchestration: Kubernetes, Cloud Run

 

Senior Data Engineer

• Leadership: Led the development and implementation of a data lake architecture that revolutionized data storage and retrieval, fostering efficiency and scalability across the organization.

• Leveraged Delta Lake, Databricks, and Synapse to architect a cutting-edge lakehouse solution, optimizing data storage and processing capabilities.

• ETL Transformation: Employed robust ETL processes to transform and cleanse data, achieving a remarkable 100% improvement in data quality and accuracy.

• Analytics Platform Deployment: Spearheaded the deployment of an advanced analytics platform, empowering data scientists to effortlessly access and analyze vast datasets.

• Data Catalog Implementation: Established a comprehensive data catalog to centralize metadata management and enable effective data governance practices.

• Real-time Streaming Pipeline: Engineered a high-performance real-time streaming pipeline, enabling near-instantaneous data analytics for real-time insights.

• Data Security Framework: Implemented a robust data security framework to ensure compliance with stringent data privacy regulations, safeguarding sensitive information.

• Continuous Integration/Continuous Deployment (CI/CD): Pioneered the creation of a CI/CD pipeline, significantly reducing time-to-deployment and enhancing overall operational efficiency.

• Introduced an AI-powered chatbot leveraging ChatGPT capabilities for medication ordering process streamlining.

• Developed a real-time streaming solution for receiving faxes through RingCentral and automated extraction of critical details.

• Designed and implemented an automated solution for extracting patient and medication data from any facility software.

✨Project

Technologies Utilized:

Cloud Platform: Azure

Languages: Python,C#,Java and SQL

Data Processing: Azure Databricks, Apache Spark, Apache Airflow, Azure Data Factory

Data Ingestion: Azure Data Factory, Apache Kafka, Azure Event Hubs, Azure Service Bus

Database:Azure SQL Server , Azure Cosmos DB

Data Integration: Azure Data Factory

Data Storage: Azure Blob Storage, Delta Lake, Azure Synapse

Streaming: Apache Kafka, Azure Stream Analytics, Apache Flink

Metadata Management: Apache Atlas, Apache Ranger, Azure Data Catalog

Infrastructure as Code: Azure Resource Manager (ARM) Templates, Terraform

Security: Azure Key Vault, Apache Ranger

Visualization: Power BI

CI/CD: Azure DevOps, GitHub

RPA: RPA UIPath

 

Data Engineering Manager

• Led a dynamic team Proactively drove the vision for Business Intelligence (BI) and Data Warehousing within a specific product vertical, crafting and executing a strategic plan to realize this vision.

• Defined and implemented processes essential for achieving operational excellence in data management and system reliability, ensuring the foundation and infrastructure supported scalable growth.

• Built and led a high-caliber BI and Data Warehousing team, designed to scale with the organization's needs, fostering a culture of excellence and continuous improvement.

• Established strong cross-functional relationships with Data Scientists, Product Managers, User Experience Researchers, and Software Engineers to deeply understand data needs and deliver comprehensive data solutions.

• Managed comprehensive data warehouse strategies across the product vertical, utilizing Amazon Redshift to ensure efficient data storage, processing, and analysis capabilities.

• Spearheaded the development and operationalization of a data lake on Amazon S3, optimizing data storage, integration, and accessibility across the organization.

• Drove the design, building, and launching of new data models and data pipelines in production, enhancing data availability and analytic capabilities.

• Led the development of data resources, supporting new product launches and enabling data-driven decision-making processes.

• Championed data quality across the product vertical and related business areas, implementing robust data governance and quality assurance practices.

• Managed the delivery of high-impact dashboards and data visualizations, transforming complex datasets into actionable insights for stakeholders.

• Defined and managed SLAs for all data sets and processes running in production, ensuring high reliability and performance standards.

✨Project

Technologies Utilized:

Cloud Platform: AWS

Languages: Python,C#,Java and SQL

Data Processing: Kafka ,AWS Glue, Amazon EMR ,PySpark

Data Steaming: Amazon Kinesis

Compute: AWS Lambda, Amazon EC2

Data Ingestion: Apache Airflow

Database:Amazon RDS, Amazon DynamoDB, SQL Server, Elasticsearch

Data Storage: AWS S3, Amazon Redshift ,SQL Server

Metadata Management: Apache Atlas, Apache Ranger

Infrastructure as Code: Terraform

Visualization: Power BI , Qlik Sense

CI/CD: Git, GitHub, Jenkins

Visualization and BI Tools: Apache Superset ,Grafana

Data Engineering Supervisor

• Team Leadership and Mentorship: Built and led a high-performing team of data engineers, fostering an environment of innovation, continuous learning, and professional development.

• Spearheaded the development and optimization of complex ETL processes using Talend, and Python, significantly improving data integration efficiency and system interoperability.

• Led the strategic development and successful implementation of new service offerings for a TE Mobile operator, directly contributing to enhanced product market fit and customer satisfaction.

• Scalable Data Streaming Architecture: Designed and deployed a high-performance data streaming solution, facilitating real-time data analytics and insights, thereby supporting critical decision-making processes.

• Applied sophisticated computational techniques to analyze large datasets, employing algorithms that produced actionable insights and findings, driving business growth and operational efficiency.

• Established rigorous data validation frameworks to ensure the accuracy and reliability of all data collected, laying the foundation for trustworthy analytics and reporting.

✨Project

Technologies Utilized:

Apache Kafka, Apache Airflow, Docker, Kubernetes, Elasticsearch, Python, R, PySpark, Grafana, Apache Hadoop, Apache Flink, Apache Beam, Apache Cassandra, Apache HBase, Apache Druid, Apache NiFi, Apache Superset, Apache Arrow, Apache Arrow Flight, Apache Parquet, Apache Avro, Apache Lucene, Apache Solr, Apache Mahout, Apache ZooKeeper, Apache Samza, Apache Iceberg, Apache Pulsar, Apache Calcite, Apache Pig, Apache Tez, Talend Open Studio, Pentaho Data Integration (Kettle), Apache NiFi

Senior Data Engineer

• Led architecture and development of a large-scale data lake capable of ingesting millions of records per minute to enable advanced analytics.
• Leveraged Kafka, Pulsar, NiFi, Airflow to build highly scalable and automated data pipelines
• Designed infrastructure on Docker and Kubernetes for fault tolerance and easy management
• Established data governance standards and best practices for data quality and compliance

• Directed a team of 10 data engineers, promoting collaboration and continuous improvement of data systems.

• Conducted rigorous data validation checks to ensure accuracy and reliability for business reports.

• Optimized ETL processes on Hadoop using Talend, enhancing workflow efficiency by 40%.

• Implemented master data management using Talend to establish consistent, high-quality data.

• Partnered with business leaders to translate analytics needs into technical requirements and data engineering solutions.

✨Project

Technologies Utilized:

Apache Kafka, Apache Airflow, Docker, Kubernetes, Elasticsearch, Python, R, PySpark, Grafana, Apache Hadoop, Apache Flink, Apache Beam, Apache Cassandra, Apache HBase, Apache Druid, Apache NiFi, Apache Zeppelin, Apache Sqoop, Apache Storm, Apache Ignite, Apache Kylin, Apache Superset, Apache Arrow, Apache Arrow Flight, Apache Parquet, Apache Avro, Apache Lucene, Apache Solr, Apache Mahout, Apache ZooKeeper, Apache Samza, Apache Iceberg, Apache Pulsar, Apache Calcite, Apache Pig, Apache Tez, Talend Open Studio, Pentaho Data Integration (Kettle), Apache NiFi

Data Engineer

• Hadoop-based Data Lake Construction: Architected and built an open-source data lake on the Hadoop ecosystem, tailored to handle massive data volumes with millions of records ingested per minute. This project involved:System Design: Crafting a scalable and resilient architecture capable of processing and storing vast amounts of data efficiently.

• Data Ingestion: Implementing high-throughput data ingestion pipelines to accommodate real-time data flow from multiple sources, ensuring robustness and reliability.

• Data Management: Establishing comprehensive data management practices, including data cataloging, security, and governance, to maintain data quality and accessibility.

• Analytics Integration: Enabling advanced analytics capabilities by integrating analytical tools and platforms, facilitating deep insights and data-driven decision-making across the organization.

• SQL Server Database Management: Led the design, development, and maintenance of a SQL Server relational database, implementing data warehousing best practices to optimize data storage, retrieval, and analysis.

• .NET Application Development: Spearheaded the development and management of .NET applications, adhering to industry best practices to ensure robustness, efficiency, and scalability.

• Automatic Reporting Systems: Engineered and managed automatic reporting systems using SQL Server Integration Services (SSIS), enhancing business intelligence and decision-making processes.

• Database Migration: Directed migration tasks across various database platforms using SSIS, ensuring seamless data transfer, integrity, and minimal downtime.

• SSAS OLAP Database: Developed and managed an SSAS OLAP database, applying data warehousing and BI best practices to support complex analytical queries and data analysis.

✨Project

Technologies Utilized:

Apache Kafka, Apache Airflow, Docker, Kubernetes, Elasticsearch, Python, R, PySpark, Grafana, Apache Hadoop, Apache Flink, Apache Beam, Apache Cassandra, Apache HBase, Apache Druid, Apache NiFi, Apache Zeppelin, Apache Sqoop, Apache Storm, Apache Ignite, Apache Kylin, Apache Superset, Apache Arrow, Apache Arrow Flight, Apache Parquet, Apache Avro, Apache Lucene, Apache Solr, Apache Mahout, Apache ZooKeeper, Apache Samza, Apache Iceberg, Apache Pulsar, Apache Calcite, Apache Pig, Apache Tez, Talend Open Studio, Pentaho Data Integration (Kettle), Apache NiFi

Data Developer

• ETL Development and Optimization: Led hands-on development and optimization of ETL processes, ensuring efficient data extraction, transformation, and loading workflows. Utilized SSIS and custom scripting to automate data flows, enhancing data quality and availability.

• Reporting and Analytics: Designed and implemented insightful reports using SQL Server Reporting Services (SSRS), enabling stakeholders to access timely, accurate data for strategic decision-making. Developed dashboards and visualizations that clearly communicated key metrics and trends.

• Data Warehousing Modeling & Design: Spearheaded DW modeling and design initiatives, employing dimensional modeling techniques and best practices to structure data for optimal analysis and reporting.

• Query Performance Optimization: Applied in-depth knowledge of SQL and database management principles to optimize query performance, significantly reducing response times and improving user experience for data-intensive applications.

• Advanced Analytics on Big Data: Leveraged mathematical, statistical, and machine learning methods to analyze big data, using high-performance computing tools like Hadoop and Spark. Developed models and algorithms that translated complex datasets into actionable insights, supporting critical business decisions.

• Legacy Data Warehouse Modernization: Successfully remodeled a legacy data warehouse, transitioning it to a modern architecture based on industry best practices. This project involved comprehensive data architecture revision, migration planning, and execution, resulting in a more scalable, efficient, and reliable data warehousing solution.

✨Project

Technologies Utilized:

Apache Kafka, Apache Airflow, Docker, Kubernetes, Elasticsearch, Python, R, PySpark, Grafana, Apache Hadoop, Apache Flink, Apache Beam, Apache Cassandra, Apache HBase, Apache Druid, Apache NiFi, Apache Zeppelin, Apache Sqoop, Apache Storm, Apache Ignite, Apache Kylin, Apache Superset, Apache Arrow, Apache Arrow Flight, Apache Parquet, Apache Avro, Apache Lucene, Apache Solr, Apache Mahout, Apache ZooKeeper, Apache Samza, Apache Iceberg, Apache Pulsar, Apache Calcite, Apache Pig, Apache Tez, Talend Open Studio, Pentaho Data Integration (Kettle), Apache NiFi

TECHNOLOGY SUMMARY

Programming languages

Architecture

Databases

Education

Bachelor's Degree in Computer Systems Engineering

Languages

Arabic 🇪🇬

English 🇺🇸

🏆 Certifications

🏆 Awards and Honors

• We Telecom Egypt Best Employee 2020

• Top Data and Analytics Influencer by KDnuggets - 2020

• Telecom Egypt IT Best Employee 2018

• TEData Best Employee 2017

• TEData Best Employee 2016

• TEData Best Employee 2015

• TEData Best Employee 2014

Additional Information

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