Nearly 3+ years of professional expertise in Data Engineering, and 5+ years in IT encompassing Data Modeling, Data Mining, Data Cleaning, Data Visualization, and constructing Data Pipelines
Expertise in creating data pi…
Nearly 3+ years of professional expertise in Data Engineering, and 5+ years in IT encompassing Data Modeling, Data Mining, Data Cleaning, Data Visualization, and constructing Data Pipelines
Expertise in creating data pipelines in Azure Data Factory enabling seamless data movement and transformation across on-premises and cloud environments, and facilitating data-driven insights for the organization
Well-versed in data processing pipelines using Azure Databricks, leveraging advanced technologies such as Spark, Scala, and PySpark to transform large-scale datasets into actionable business insights
Leveraged Azure Synapse to consolidate data sources, enabling efficient data processing, real-time insights, and data-driven decision-making for the organization
Proficient in SQL (Structured Query Language) with a strong track record of writing complex queries, optimizing database performance, and leveraging data for strategic decision-making, contributing to efficient data management and analysis
Orchestrated seamless data integration across diverse systems and platforms, ensuring real-time data availability and accuracy, leading to enhanced decision-making and operational efficiency
Accomplished Azure Key Vault to manage over 100 encryption keys and secrets, ensuring data security and achieving compliance rating during audits
Skilled in leveraging Azure Logic Apps to streamline business processes, enhance efficiency, and drive digital transformation initiatives
Experienced in working with Snowflake as a cloud-based data warehouse platform and integrating it with other Azure services, including Azure Data Factory, Azure Data Lake, and Azure Databricks
Proficient in using SQL Server Integration Services (SSIS) for designing, developing, and managing ETL (Extract, Transform, Load) processes, ensuring efficient data integration and workflow automation
Competent in planning and executing complex data migration projects, ensuring seamless and secure data transfer with minimal downtime
Versatile in data integration techniques, adept at harmonizing diverse data sources into a cohesive and organized format, enabling data-driven decision-making and contributing to improved operational efficiency
Experienced in developing, maintaining, and processing large databases with complex relationships between tables, written several advanced SQL queries for extracting relevant data for predictive analytics
Worked in an Agile environment and gained insight into Agile methodologies and Lean working techniques. Participated in Agile ceremonies and Scrum Meetings
Designed and implemented end-to-end data pipelines using Azure Data Factory, Azure Data Lake Storage, and Azure SQL to enable efficient data ingestion and processing reducing data processing time
Collaborated with data scientists to develop scalable data processing workflows using Azure Databricks and PySpark for advanced analytics and analyze 1 million records per minute, resulting in more accurate predictive models and improved decision-making
Managed data security and encryption through Azure Key Vault to ensure compliance and safeguard sensitive information compliance rate and zero data breaches during tenure
Leveraged Snowflake schema design principles for efficient data modeling and improved query performance, reducing report generation time and enhancing data accessibility for stakeholders
Administered and optimized Azure SQL databases, including performance tuning, query optimization, and disaster recovery planning resulting reduction in query execution time
Worked closely with business stakeholders to understand requirements and implemented data solutions to support their objectives
Designed and implemented data warehousing solutions using Azure Synapse Analytics, improving data accessibility and reporting capabilities for the organization
Implemented Azure Data Lake Gen2 and Azure SQL Data Warehouse for efficient storage and processing of large-scale data
Utilized Python for data analysis and automation, reducing manual data processing tasks by 30% and improving data accuracy and reporting efficiency
Implemented CI/CD pipelines using tools like Jenkins and Azure DevOps, enabling automated testing and seamless deployments, reducing release cycle time and increasing software quality
Designed and maintained SSIS packages to automate data extraction, transformation, and loading (ETL) processes, resulting a reduction in data processing time and improved data accuracy
• Designed and implemented end-to-end data pipelines using Azure Data Factory, Azure Data Lake Storage, and Azure SQL to enable efficient data ingestion and processing reducing data processing time
• Collaborated with data scientists to develop scalable data processing workflows using Azure Databricks and PySpark for advanced analytics and analyze 1 million records per minute, resulting in more accurate predictive models and improved decision-making.
• Managed data security and encryption through Azure Key Vault to ensure compliance and safeguard sensitive information compliance rate and zero data breaches during tenure
• Leveraged Snowflake schema design principles for efficient data modeling and improved query performance, reducing report generation time and enhancing data accessibility for stakeholders
• Administered and optimized Azure SQL databases, including performance tuning, query optimization, and disaster recovery planning resulting reduction in query execution time
• Worked closely with business stakeholders to understand requirements and implemented data solutions to support their objectives
• Designed and implemented data warehousing solutions using Azure Synapse Analytics, improving data accessibility and reporting capabilities for the organization
• Implemented Azure Data Lake Gen2 and Azure SQL Data Warehouse for efficient storage and processing of large-scale data
Designed and maintained relational databases with SQL queries, ensuring efficient data storage and retrieval to improve database performance and reduce query execution time
Extracted data from various sources, including flat files, spreadsheets, external databases and Transformed data to meet specific business requirements before loading it into the database
Created and maintained data models, including entity-relationship diagrams and database schemas to ensure data models align with business requirements and are scalable for future needs
Performed routine database maintenance tasks such as backups, indexing, and data integrity checks by Managing user access control and security, ensuring data confidentiality and compliance with regulations
Assisted data analysts and business analysts in extracting meaningful insights from data to Generate ad-hoc reports for stakeholders using SQL reporting tools
Identified and addressed performance issues, optimizing database configurations, and making recommendations for hardware or software upgrades when necessary to maintain optimal performance
Maintained comprehensive documentation of database schemas, data dictionaries, and SQL scripts for future reference and team collaboration
Participated in database migration projects, ensuring a seamless transition of data and SQL code from one environment to another, minimizing downtime and data loss
Documented database schemas, SQL code, and processes, facilitating knowledge sharing and ensuring compliance with best practices
Collaborated with software developers to integrate SQL code with applications, ensuring seamless data connectivity and a consistent user experience
Automated routine tasks and reporting processes by developing SQL scripts and scheduled jobs, reducing manual effort and increasing operational efficiency
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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