
Results-driven Software Engineer with expertise in Java development, cloud computing, and data engineering. Skilled in designing and optimizing ETL pipelines, database management, and implementing scalable data solutions using AWS,GCP, and Apache Spark. Experienced in backend and frontend development, including Angular, and proficient in CI/CD practices, version control, and performance optimization. Strong background in data warehousing, machine learning,NLP, and business intelligence tools like Power BI. Adept at leveraging AI and data analytics to drive business efficiency and innovation.
Developed enhancements for SP Connect Website Application.
Resolved software bugs to enhance functionality.
Enhanced and optimized web pages.
Steered the transition from Angular 8 to Angular 16.
Executed POC projects utilizing Aspose Slides for PPT generation.
Implemented solutions for security flaws in Java 11.
Set up tracking tools in Google Analytics tailored to SP Connect application's performance needs.
Upgraded MongoDB to latest version, ensuring database remains active.
Facilitated migration of approximately 20K+ files from Solr to Opensearch database.
Executed deployment strategies using Jenkins and Terraform.
Leveraged AWS Athena for data querying and analysis.
Utilized AWS Glue for ETL jobs and efficient data transformation.
Conducted Python scripting in tandem with S3 for seamless data curation.
Spearheaded upgrade from Java 11 to Java 21.
Developed Swagger-UI implementation in Java enabling creation of mock controllers and services using
YAML/JSON.
Managed diverse tasks in both backend and frontend roles proficiently.
Oversaw database operations with efficient curation and design.
Crafted precise ER diagrams to represent data relationships.
Worked closely with systems analysts, engineers and programmers to understand limitations, develop capabilities
and resolve software problems.
Designed databases to store application data using SQL Server or MongoDB technologies.
Streamlined data flow from diverse sources using ETL tools such as Talend, Informatica, and Airflow.
Analyzed user requirements, designed and developed ETL processes to load enterprise data into the Data
Warehouse.
Worked with cross-functional teams to achieve goals.
Configured and maintained cloud-based data infrastructure on platforms like AWS, Azure, and Google Cloud to
enhance data storage and computation capabilities.
Developed Python scripts for extracting data from web services API's and loading into databases.
Engineered a dynamic tracking system to capture clicks and shares accurately.
Java/C/Python Programming
Database management
ETL processes
Angular framework
Cloud infrastructure
Performance optimization
Data analysis
Technical documentation
Data extraction
Advanced Microsoft office
Deadline driven
Data warehousing
Python scripting
Data transformation
Data science agility
AWS cloud services
AWS glue ETL management
ETL design and implementation
Apache Spark mastery
Lambda functions
Data warehousing solutions
Amazon S3 proficiency
NoSQL databases
PowerBI reporting
Data pipeline development
Natural language processing
Machine learning
JIRA
Source and version control: git, github
Data querying
Power BI
Google Cloud Platform
Data Engineering Pipeline Management with
Apache Airflow
AI for Business Strategy
Artificial Intelligence Basics
AWS Cloud Practitioner
Analyzing and Visualizing Data with Microsoft Power BI
Artificial Intelligence and Business Strategy
Data Engineering Foundations
Data Engineering Pipeline Management with Apache Airflow
Data Pipeline Automation using R & Python
Data Science on Google Cloud Platforms
NLP with Python for Machine Learning
Oracle Database 11g: Advanced PL/SQL
Problem Solving Strategies in Data Engineering
Introduction to Artificial Intelligence