Shravan Kumar N Email & Phone Number

Atlanta, Georgia, United States

• Expertly executed data transformation in Azure Data Lake Storage Gen-2 with medallion architecture, revolutionizing workflows, elevating data quality, and driving efficient decision-making in the Azure cloud environment.
• Orchestrated seamless integration between on-premises and cloud data platforms leveraging Azure Data Factory, enacting complex transformations, and optimizing data loads into Snowflake.
• Designed and implemented high-performance ETL transformations and rigorous… Show more
• Designed and implemented high-performance ETL transformations and rigorous validation processes using Spark-SQL and Data Frames within the Azure Databricks and Azure Data Factory environments.
• Exceptionally collaborative team player, proactively partnering with Azure Logic Apps administrators and DevOps engineers for seamless monitoring and swift resolution of automation and data pipeline issues.
• Proficient in writing and maintaining YAML configuration files for data pipeline orchestration.

• Led and executed comprehensive data migration strategies, efficiently transferring mission-critical databases to Azure Data Lake, improving data accessibility and scalability.
• Enhanced Spark performance by optimizing data processing algorithms, and leveraging techniques such as partitioning, caching, and broadcast variables.
• Strategically orchestrated the seamless data ingestion of an extensive 3 billion records into a suite of Azure Services, leveraging Azure Databricks to achieve… Show more
• Strategically orchestrated the seamless data ingestion of an extensive 3 billion records into a suite of Azure Services, leveraging Azure Databricks to achieve a notable 40% enhancement in data processing speed.
• Pioneered migrating on-premises Oracle ETL processes to Azure Synapse Analytics, substantially improving data processing efficiency and cost-effectiveness.
• Directed the strategic transference of SQL databases to Azure Data Lake and SQL Data Warehouse, employing Azure Data Factory to ensure optimal data transfer and storage solutions.

• Strategically architected and deployed an enterprise-grade Data Lake, facilitating advanced analytics, processing, storage, and reporting on high-velocity, large-scale data sets.
• Managed and optimized data storage and loading procedures for Azure BLOB and Azure Data Lake storage systems, ensuring seamless integration with Azure SQL Synapse Analytics.
• Optimized data processing efficiency using Spark SQL for Scala and Python, enabling seamless RDD to Data Frame conversions… Show more
• Optimized data processing efficiency using Spark SQL for Scala and Python, enabling seamless RDD to Data Frame conversions, significantly accelerating analysis and system performance. Streamlined data manipulation.

• Designed and implemented scalable AWS infrastructure utilizing services like EC2, S3, and Lambda for efficient data processing and storage.
• Successfully implemented DBT modeling in a large-scale data warehouse migration project, transforming legacy ETL processes into modern, modular DBT models, resulting in improved data quality and reduced processing time.
• Build Self-service data pipelines using AWS Services like SNS, StepFunction, Lambda, Glue, EMR, EC2, Athena, Sage Maker,… Show more
• Build Self-service data pipelines using AWS Services like SNS, StepFunction, Lambda, Glue, EMR, EC2, Athena, Sage Maker, Quick Sight, Redshift, etc.
• successfully designed and implemented a robust data pipeline using Snowflake, enabling efficient processing and analysis of large-scale datasets for actionable insights.
• Moved large amounts of data from AWS S3 buckets to AWS Redshift using Glue and EMR.

• Used AWS services like AWS Services like SNS, StepFunction, Lambda, Redshift, Glue, EMR, EC2, Athena, etc.
• Utilized NumPy and pandas to efficiently process and analyze large datasets, enabling streamlined data engineering workflows.
• Cleaned data and processed third-party spending data into maneuverable deliverables within specific formats with Excel macros and Python libraries.
• Gathering business requirements by organizing and managing meetings with business stakeholders and IT… Show more
• Gathering business requirements by organizing and managing meetings with business stakeholders and IT analysts on a scheduled basis.
• Analyzed the business requirements by dividing them into subject areas and understood the data flow.