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.
<p>Collaborated with business analysts to gather and analyze project requirements, resulting in a 20% improvement in data accuracy.<br>
Engineered Azure Data Factory pipelines for data extraction and ingestion from various source systems, enhancing data processing efficiency by 40%.<br>
Accelerated data engineering workflows by designing and implementing customized Azure DevOps CI/CD pipelines, enhancing data integration, transformation, and deployment efficiency across projects.<br>
Developed Azure Databricks notebooks utilizing PySpark-SQL for effective data transformation and aggregation, reducing processing time by 30%.<br>
Maximized data management efficiency in Lakehouse Medallion architecture using modern data engineering techniques for storage, processing, and analysis.<br>
Established Delta Lake Tables and orchestrated the loading of files using PySpark notebooks, resulting in a 25% increase in data retrieval speed.<br>
Documented data pipelines, models, and Power BI reports, resulting in a reduction in onboarding time.<br>
Facilitated the PowerBI Reporting team, ensuring timely and accurate reporting for strategic decision-making.</p>
<p>Utilized SQL to proficiently extract and transform data from diverse data sources, facilitating seamless data retrieval for reporting purposes.<br>
Developed SQL stored procedures, triggers, functions, tables, and views, including complex queries using CTE.<br>
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.<br>
Applied fundamental statistical analysis techniques to dissect data, identifying trends, patterns, and anomalies which contributed valuable insights to support data-driven decision-making.<br>
Developed, maintained, and automated ETL pipelines using Azure Data Factory and Databricks to prepare for reporting and dashboards.<br>
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.<br>
Implemented automated reporting solutions, significantly reducing manual effort and improving reporting efficiency.</p>
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