Nalla Raviteja

Gangavathi,India

Summary

Results-driven Data Engineer with 6+ years of expertise in Azure, AWS, SQL Development, and Business Intelligence Solutions. Proven ability to design, develop, and optimize OLTP and Data Warehousing systems using Microsoft and AWS technologies. Adept at Azure Data Factory (ADF), Databricks, Event Hub, DevOps, AWS S3, Redshift, Glue, Lambda, and Big Data processing. Strong background in performance tuning, ETL development, and cloud-based data engineering. A collaborative professional with excellent analytical and leadership skills to drive data-driven decision-making.

Equipped with strong problem-solving abilities, willingness to learn, and excellent communication skills. Poised to contribute to team success and achieve positive results. Ready to tackle new challenges and advance organizational objectives with dedication and enthusiasm.

Overview

years of professional experience

Work History

Associate Manager (Data Engineering)

Tredence Analytics Solutions Pvt Ltd

09.2024 - Current

Designed high-performance data pipelines integrating Azure
Developed real-time and batch ETL workflows using Azure Data Factory
Led data security implementation with Azure Key Vault
Collaborated with cross-functional teams to ensure seamless data migration and transformation

Azure & AWS Data Engineer

Adroit Software Solutions Pvt Ltd

09.2018 - 08.2024

Designed OLTP and OLAP systems using star schema models and AWS Redshift
Developed ETL workflows using SSIS, Azure Data Factory, and AWS Glue
Integrated streaming data from Event Hub and Kafka for real-time processing
Automated data validation and quality checks using Python and SQL scripts
Created data comparison dashboards in Power BI and AWS QuickSight

Skills

T-SQL
PL/SQL
Dynamic SQL
Python
MS SQL Server
Oracle
AWS Redshift
MS Access
Azure SQL
Azure Data bricks
Azure Key Vault
Azure Pipelines
AWS S3
AWS Glue
AWS Lambda
SSRS

SSIS
SSAS
Azure Data Factory
Power BI
Spark
PySpark
Event Hub
Kafka
Terraform
Kubernetes
Team Foundation Server
Jenkins
Git
Star Schema
Fact-Dimension Modeling
Data Normalization

Projects Achievements

Optimized Data Pipelines: Reduced data processing latency by 40% by implementing performance enhancements in Azure Data Factory and AWS Glue.
Automated ETL Monitoring: Developed an alerting system for data pipeline failures, reducing downtime and improving operational efficiency.
Cloud Migration Success: Led a zero-downtime cloud migration of on-premises databases to Azure SQL and AWS Redshift.

Disclaimer

I hereby declare that the information furnished above is true and correct to the best of my knowledge and belief.

Timeline