Data Engineer with experience in Azure Data Factory, Azure Databricks, PySpark-SQL, Power BI, and SQL. Has worked on data extraction, ingestion, transformation, ETL/ELT pipelines, and reporting, with experience in data a…
Data Engineer with experience in Azure Data Factory, Azure Databricks, PySpark-SQL, Power BI, and SQL. Has worked on data extraction, ingestion, transformation, ETL/ELT pipelines, and reporting, with experience in data analysis and dashboard development.
• Collaborated with business analysts to gather and analyze project requirements, resulting in a 20% improvement in
data accuracy.
• Engineered Azure Data Factory Pipelines for data extraction and ingestion from various source systems, enhancing
data processing efficiency by 40%.
• Accelerated data engineering workflows by designing and implementing customized Azure DevOps CI/CD pipelines,
enhancing data integration, transformation, and deployment efficiency across projects.
• Developed Azure Databricks notebooks utilizing PySpark-SQL for effective data transformation and aggregation,
reducing processing time by 30%.
• Maximized data management efficiency in Lakehouse Medallion architecture using modern data engineering
techniques for storage, processing, and analysis.
• Established Delta Lake Tables and orchestrated the loading of files using PySpark notebooks, resulting in a 25%
increase in data retrieval speed.
• Documented data pipelines, models, and Power BI reports, resulting in a reduction in onboarding time.
• Facilitated the PowerBI Reporting team, ensuring timely and accurate reporting for strategic decision-making.
Collaborated with business analysts to gather and analyze project requirements, resulting in a 20% improvement in data accuracy.
Engineered Azure Data Factory pipelines for data extraction and ingestion from various source systems, enhancing data processing efficiency by 40%.
Accelerated data engineering workflows by designing and implementing customized Azure DevOps CI/CD pipelines, enhancing data integration, transformation, and deployment efficiency across projects.
Developed Azure Databricks notebooks utilizing PySpark-SQL for effective data transformation and aggregation, reducing processing time by 30%.
Maximized data management efficiency in Lakehouse Medallion architecture using modern data engineering techniques for storage, processing, and analysis.
Established Delta Lake Tables and orchestrated the loading of files using PySpark notebooks, resulting in a 25% increase in data retrieval speed.
Documented data pipelines, models, and Power BI reports, resulting in a reduction in onboarding time.
Facilitated the PowerBI Reporting team, ensuring timely and accurate reporting for strategic decision-making.
Utilized SQL to proficiently extract and transform data from diverse data sources, facilitating seamless data retrieval for reporting purposes.
Developed SQL stored procedures, triggers, functions, tables, and views, including complex queries using CTE.
Successfully designed, developed, and maintained interactive reports and dashboards, primarily focusing on Power BI, and conveyed critical insights to stakeholders through visually appealing and user-friendly reports.
Applied fundamental statistical analysis techniques to dissect data, identifying trends, patterns, and anomalies which contributed valuable insights to support data-driven decision-making.
Developed, maintained, and automated ETL pipelines using Azure Data Factory and Databricks to prepare for reporting and dashboards.
Customized and designed data visualizations and charts within Power BI, enhancing the clarity and impact of reports and ensuring reports met end-users’ needs and expectations.
Implemented automated reporting solutions, significantly reducing manual effort and improving reporting efficiency.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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