Nearly 5 years of dedicated IT experience as an Azure Data Engineer and also worked with Azure Services like Azure Data Factory, Azure Synapse, Azure Data bricks platforms
Knowledgeable in optimizing SQL queries in Azure…
Nearly 5 years of dedicated IT experience as an Azure Data Engineer and also worked with Azure Services like Azure Data Factory, Azure Synapse, Azure Data bricks platforms
Knowledgeable in optimizing SQL queries in Azure Database, achieving reduction in query execution times in which enhancement translates into faster data retrieval, ensuring timely access to critical information and improved application performance
Versatile in Data ingestion in Azure Data Factory, achieving reduction in data loading time through optimized data transfer and transformation processes, ensuring timely availability of critical data
Skilled in managing data storage in Azure Data Lake Storage, optimizing storage costs by implementing data lifecycle policies and achieving a reduction in storage expenses while ensuring 85% data availability and accessibility
Proficient in reducing the average of achieving query execution time for data warehouse queries implementing schema design optimizations, data loading enhancements, and query tuning techniques
Experienced in Azure Synapse Analytics for data warehousing, achieving a reduction in query response times, ensuring faster data access, and enabling data-driven decisions
Extensive experience in designing, implementing, and optimizing Azure Cosmos DB solutions for mission-critical applications and proficient in data Modeling, partitioning strategies, and query optimization
Leveraged Snowflake in a leading cloud-based data warehousing platform, to architect and manage scalable and high-performance data solutions, enabling data-driven decision-making and analytics
Dynamic in creating compelling data visualizations and dashboards using Power BI to enable increase in the number of data-driven decisions made by stakeholders within the organization
Utilized Azure Data Explorer to harness real-time data analytics, achieving a reduction in query response times and enabling data-driven insights for faster decision-making
Well-Versed in data processing workflows in Azure Databricks, achieving a reduction in processing time through parallelized data transformations and efficient cluster management, enabling data insights delivery
Leveraged PySpark to analyse and process large-scale datasets to its distributed computing capabilities in building data pipelines, performing data transformations
Adept in implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines, ensuring efficient and automated data deployment processes, enabling faster delivery of data-driven insights
Efficient in orchestrate ETL processes within Azure Data Factory pipelines, optimizing data transformation workflows and achieving a reduction in processing time, ensuring efficient data analytics
Detail-Oriented in data processing workflows in Azure HDInsight, achieving a reduction in processing time with distributed computing for efficient data analysis, ensuring timely insights delivery
Good in Jira & Confluence for Agile project management, including sprint planning, issue tracking, and workflow customization, to ensure efficient project execution among cross-functional teams
• Orchestrated and maintained Azure data pipelines, ensuring timely availability of critical data for analytics and decision-making
• Developed Azure Data Factory pipelines to increase the effectiveness of data transmission and shorten pipeline execution times, enabling quicker access to vital business insights data
• Designed and managed ETL workflows using Azure Data Factory, enhancing overall data processing efficiency and timeliness of insights delivery
• Utilized Snowflake data warehouse platform to optimize data storage, processing, and analytics, resulting in improved data accessibility and actionable insights for decision-making
• Implemented Azure Data Lake Storage for data orchestration, enhancing data availability and accessibility
• Optimized Azure Blob Storage by implementing data lifecycle policies and optimizing data storage tiers while ensuring data availability
• Developed Azure Synapse Analytics for data warehousing, enabling faster data-driven decision-making across the organization
• Managed Azure HDInsight clusters, optimizing data processing workflows while ensuring high availability and performance
• Managed Azure SQL Database environments, achieving an improvement in query performance through indexing and query optimization, ensuring efficient data retrieval and analysis
Orchestrated and maintained Azure data pipelines, ensuring timely availability of critical data for analytics and decision-making
Developed Azure Data Factory pipelines to increase the effectiveness of data transmission and shorten pipeline execution times, enabling quicker access to vital business insights data
Designed and managed ETL workflows using Azure Data Factory, enhancing overall data processing efficiency and timeliness of insights delivery
Utilized Snowflake data warehouse platform to optimize data storage, processing, and analytics, resulting in improved data accessibility and actionable insights for decision-making
Implemented Azure Data Lake Storage for data orchestration, enhancing data availability and accessibility
Optimized Azure Blob Storage by implementing data lifecycle policies and optimizing data storage tiers while ensuring data availability
Developed Azure Synapse Analytics for data warehousing, enabling faster data-driven decision-making across the organization
Managed Azure HDInsight clusters, optimizing data processing workflows while ensuring high availability and performance
Managed Azure SQL Database environments, achieving an improvement in query performance through indexing and query optimization, ensuring efficient data retrieval and analysis
Improved Azure Data Factory pipelines to which reduced ETL processing times and improved the efficiency and speed of data delivery for crucial business operations
Created data compression and tiering techniques, data lake storage solutions were implemented on Azure, resulting in decrease in storage costs while maintaining good data availability and accessibility.
Created the Azure Data Catalog to manage and Catalog of the data assets in our business, increasing data discoverability and cutting down on time spent looking for resources
Designed Azure Databricks for data processing, which cut down on data transformation times and increased the effectiveness of the data workflow as a whole
Leveraged advanced SQL techniques to optimize complex queries, enabling faster data access and analysis
Built and managed big data clusters using Azure HDInsight, which reduced processing costs and allowed for the effective processing and analysis of enormous datasets
The AI-first Recruitment Operating System that unifies and automates the entire hiring lifecycle for modern enterprises worldwide.
Dr Job FZ LLC. 2026 © All Rights Reserved
