Senior .NET Backend Engineer with Azure Expertise

Naveen Bondhu

+1-972-***-**** Email: ****************@*****.***

PROFESSIONAL SUMMARY:

Senior .NET Developer & Data Analyst with 6+ years of experience delivering enterprise backend systems and data-driven analytics solutions. Strong expertise in C#, .NET Core, ASP.NET Web API, Azure Cloud, combined with advanced analytics skills in SQL, Python, R, Power BI, and Excel. Proven success in building scalable APIs, optimizing databases, designing ETL pipelines, developing dashboards, and delivering actionable insights across retail, healthcare, and government domains. Adept at bridging engineering and analytics to support data-driven decision-making in Agile environments.

TECHNICAL SKILLS:

Programming & Backend: C#, .NET Core, .NET Framework, ASP.NET MVC, ASP.NET Web API, REST & SOAP APIs, Multithreading, API Security, JSON/XML

Frontend: React, JavaScript, HTML5, CSS3, Bootstrap, Responsive UI Design

Data Analytics & BI: SQL, Python (Pandas, NumPy, Matplotlib, Seaborn), R (dplyr, ggplot2), Power BI (DAX, Power Query, Data Modeling), Tableau, Excel Dashboards

Databases & Warehousing: SQL Server, PostgreSQL, DB2, MySQL, AWS RDS, Redshift, Snowflake, Stored Procedures, Query Optimization, Indexing

ETL & Data Pipelines: Python ETL, SQL ETL, Power Query, Azure Data Factory (Basic), AWS Glue (Basic), API Integration, Data Cleansing, Scheduled Jobs

Cloud & DevOps: Azure App Services, Azure Functions, Azure API Management, Azure DevOps, AWS (S3, EC2, IAM), Git, GitHub, Jenkins, Docker, Kubernetes

Messaging & Monitoring: IBM MQ (Async/Sync), Splunk, Azure Monitor, Application Insights, Postman, ServiceNow, and Jira

Statistics & ML: EDA, Hypothesis Testing, Correlation, Regression, Forecasting, Classification (Basic), Feature Engineering

PROFFESSIONAL EXPERIENCE:

Client: Neucore Technologies Feb 2023 - Present

Associate Dot Net Developer Associate Data Analyst

Responsibilities:

.NET / Backend Responsibilities:

Developed scalable backend services using C#, .NET Core, ASP.NET Web API for high-volume transactional systems.

Designed and deployed Azure App Services, Azure Functions, API Management, and Key Vault integrations.

Implemented API versioning, throttling, logging, and monitoring using APIM and Application Insights.

Built and supported IBM MQ message flows for reliable async and sync communication.

Optimized DB2 and SQL Server stored procedures, indexing strategies, and query performance.

Automated CI/CD pipelines using Azure DevOps YAML, improving deployment reliability.

Performed root-cause analysis for production issues across APIs, MQ queues, databases, and cloud services.

Data Analytics Responsibilities:

Analyzed retail and healthcare datasets to identify cost-optimization opportunities and operational inefficiencies.

Built Power BI dashboards with DAX measures, KPIs, drilldowns, and row-level security.

Designed and automated ETL pipelines using Python and SQL, reducing manual reporting effort by 60%.

Conducted EDA, trend analysis, forecasting, and variance analysis for strategic planning.

Created star and snowflake data models for analytics and reporting use cases.

Leveraged AWS (S3, EC2, RDS) for analytics workloads and cloud-based reporting pipelines.

Ensured data quality through automated validation scripts and documentation.

Client: Cognizant Technology Solutions Aug 2019 – December 2023

Program Analyst Data Analyst

Responsibilities:

NET / Application Development Responsibilities

Developed enterprise backend systems using C#, ASP.NET MVC, ASP.NET Web API, and React.

Built reusable frontend components integrated with RESTful APIs.

Designed and optimized DB2 queries, stored procedures, and indexing strategies.

Implemented IBM MQ messaging with retry logic and dead-letter queue handling.

Supported CI/CD automation using Azure DevOps and Jenkins.

Participated in Agile sprints, code reviews, and performance tuning initiatives.

Data Analytics Responsibilities

Extracted, cleaned, and analyzed large datasets using SQL (DB2, SQL Server).

Built Excel and Power BI dashboards for KPI monitoring, cost analysis, and operational reporting.

Conducted root-cause analysis for data discrepancies, DB slowness, and API latency.

Integrated data from REST and SOAP APIs into analytics workflows.

Performed forecasting, trend analysis, and variance analysis for business insights.

Documented SQL scripts, ETL workflows, and dashboard usage guides.

PROJECTS:

Enterprise Order Management System

Developed scalable backend services using C#, .NET Core, ASP.NET Web API, implementing secure REST APIs with authentication, versioning, and cloud deployment on Azure.

Integrated IBM MQ (async/sync messaging) and optimized DB2 stored procedures, indexing, and SQL queriesto support 1M+ daily transactions.

Automated CI/CD pipelines using Azure DevOps and monitored application performance with Application Insights, reducing API latency by 35%.

Civil Registration System

Built secure backend modules using ASP.NET MVC and Web API to support citizen service applications and real-time status tracking.

Implemented authentication, authorization, and role-based access control (RBAC) to protect sensitive government data.

Designed optimized SQL Server schemas, stored procedures, and indexes, and developed responsive UI using React, HTML, CSS, and JavaScript

Retail Sales & Customer Analytics Dashboard

Designed interactive Power BI dashboards to analyze sales performance, customer behavior, and regional revenue trends.

Built optimized data models and DAX measures, creating KPIs, drilldowns, and executive reports.

Cleaned and transformed datasets using SQL and Power Query, enabling accurate and timely reporting.

Healthcare Claims Analysis

Extracted and analyzed large healthcare claims datasets using SQL and Python (Pandas).

Performed EDA and trend analysis to identify claim delays, anomalies, and processing bottlenecks.

Delivered insights that reduced claim processing time by 18% through data-driven recommendations.

Inventory Optimization & Forecasting

Analyzed inventory and demand data using Python, SQL, and Excel to identify consumption patterns.

Developed regression and forecasting models to improve demand planning accuracy.

Reduced excess inventory by 22% through optimized forecasting and reporting.

Customer Churn Prediction

Built churn prediction models using Logistic Regression and Random Forest algorithms.

Performed data cleaning, feature engineering, and normalization on customer usage data.

Identified key churn drivers to support proactive customer retention strategies.

Housing Market Analytics Dashboard

Developed an interactive R Shiny dashboard for real-time housing market analysis.

Processed and visualized large datasets using dplyr and ggplot2.

Enabled stakeholders to analyze pricing trends, regional patterns, and market insights.

EDUCATION:

Master of Science – Advanced Data Analytics

University of North Texas 2023 – 2024 Denton, TX

Bachelor of Technology – Electronics & Communications Engineering

Sri Venkateswara College of Engineering 2016 – 2020 Tirupati, India

CERTIFICATIONS:

C# Master Class – Udemy

ASP.NET MVC & ASP.NET Core Web API – Udemy

Microservices with .NET & REST APIs – Udemy

Microsoft Azure Fundamentals - Udemy

Microsoft Azure Data Fundamentals - Udemy

Azure DevOps CI/CD Pipelines – Udemy

Docker & Kubernetes for Developers – Udemy

AWS Cloud Practitioner Essentials - Coursera

AWS Data Analytics Fundamentals – Coursera

Microsoft Power BI - Udemy

SQL for Data Analysis – Udemy

Python for Data Analysis – Udemy

R Programming – Data Camp

Excel for Data Analytics & Business Intelligence – Udemy

ACHIEVEMENTS:

Reduced API response time by 35% through .NET API and database optimization.

Automated CI/CD pipelines using Azure DevOps, cutting deployment time by 60%.

Built Power BI dashboards with optimized DAX models, improving report performance by 40%.

Automated ETL and reporting workflows using Python and SQL, reducing manual effort by 60%.

Identified cost-optimization insights from analytics, contributing to an 18% operational cost reduction.

Optimized SQL queries and data pipelines, improving data availability and performance.

Implemented monitoring and alerting using Azure Monitor and Splunk, improving system reliability.

Delivered scalable systems handling 1M+ transactions per day with high availability.

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