Akash Vinod Butte

Software Engineer 1, MAQ Software, 07/2021 - 09/2024.|Mumbai, India

Project 1: Cloud Data Migration & ETL Optimization
Objective: Migrate data products from ADLS Gen1 to Gen2, transition U-SQL scripts to PySpark, and optimize data processing workflows.

Responsibilities:

• Migrated terabytes of data from ADLS Gen1 to Gen2, maintaining metadata integrity, security, and access controls.
• Refactored U-SQL scripts into PySpark, and implemented Delta Lake for incremental processing, reducing query execution time by 60%.
• Optimized ETL pipelines in Synapse, cutting execution time by 40%.

Project 2: On-Prem to Cloud Data Modernization.

Objective: Migrate on-premises SQL Server data warehouse to Azure while enhancing scalability, performance, and reporting capabilities.

Responsibilities:

• Performed cost analysis for Azure resources, designed, and implemented cloud-based ETL pipelines using ADF and Databricks, ensuring seamless data migration.
• Developed an incremental load strategy using Delta Lake, reducing processing time by 40%.
• Integrated Power BI with Azure SQL, improving reporting performance and data accessibility.
• Reduced on-prem SQL Server load by 50% by optimizing data ingestion and transformation workflows.

Software Engineer 2, MAQ Software, 09/2024 - Present|Mumbai, India

Project 3: Enterprise Data Reporting and Automation. Objective: Build an automated reporting system that integrates data from multiple sources to deliver real-time business insights.

Responsibilities:

• Developed ETL pipelines to extract and transform data from ADLS Gen2, SharePoint, and APIs.
• Automated report scheduling and refreshing using Power Automate workflows.
• Designed and deployed Power BI dashboards with a Tabular Model, reducing report load time, and improving performance.
• Enabled self-service analytics for business users by creating efficient data models.
  

Key Achievements Across Projects

Data Pipeline Optimization: Designed and implemented solutions using Azure Synapse Analytics, boosting data processing efficiency and reducing processing times for large-scale operations by 25%.
ETL Automation: Automated and streamlined complex ETL workflows using Azure Data Factory, improving data accuracy and reducing manual errors by 50% across multiple data sources.
CI/CD Implementation: Built and maintained CI/CD pipelines in Azure DevOps, simplifying deployment processes, achieving 99.9% system uptime, and speeding up deployment cycles.
Data Visualization: Developed interactive and dynamic Power BI dashboards, enhancing reporting efficiency and enabling stakeholders to access real-time insights for better decision-making.

Data Migration: Successfully led the migration of over 5 terabytes of data, improving processing speed, and ensuring seamless integration with minimal downtime.
Spark Optimization: Optimized Spark and PySpark jobs, reducing processing times by 40% and ensuring the system could scale effectively to handle growing data volumes.
Team Collaboration: Worked in project teams to lead and coordinate database development, determine project scopes, and resolve technical limitations.

Technologies Used Across Roles: Azure Synapse Analytics, Azure Data Factory, Databricks, Power BI, Python, Spark, PySpark, CI/CD, SSIS, Azure Logic Apps, Azure DevOps, Power Apps, and Power Automate.