CHINMAYI S N
Software EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software Engineer with 1+ years in Cloud Data Engineering & Analytics
Motivated Software Engineer with 1.6 years hands-on experience in cloud data engineering and enterprise analytics at Capgemini. Proficient in designing and deploying scalable ETL pipelines using Azure Data Factory, Microsoft Fabric, and Databricks. Skilled in Python, SQL, and data transformation workflows that support business intelligence and Power BI reporting. Certified in Microsoft Azure Fundamentals (AZ-900), Fabric Analytics Engineer (DP-600), and Azure Databricks. Strong communicator and collaborative team member with a passion for data-driven problem-solving and continuous learning in cloud and AI technologies.
Reva University
Bachelor of Engineering (B.E.) · Computer Science and Engineering
August 1, 2020 – June 30, 2024
Venkatadri Independent PU College
Pre-University Certificate · Physics, Chemistry, Mathematics, Biology (PCMB)
June 1, 2018 – May 31, 2020
Kishora Vidya Bhavana
Secondary School Leaving Certificate (SSLC) · Karnataka State Board
June 1, 2017 – May 31, 2018
Capgemini
Software Engineer (Analyst)
December 1, 2024 – Present
Bengaluru, Karnataka, India
Azure Data Analytics ETL Pipeline
April 1, 2025 – April 1, 2025
Designed and deployed a production-grade ETL pipeline migrating employee data from Azure Blob Storage to Azure SQL Database, achieving zero data loss and full pipeline automation. Implemented Slowly Changing Dimension (SCD Type 1) logic to manage and track historical employee record updates, ensuring data consistency across reporting layers. Configured linked services, datasets, and triggers in Azure Data Factory for scheduled batch ingestion; reduced manual data handling effort by automating the full pipeline. Performed large-scale data transformation and cleansing using Azure Databricks (PySpark), improving downstream data quality for BI and analytics consumption.
Farm to Folk -- Agricultural Marketplace Platform (Final Year Project)
July 1, 2023 – May 1, 2024
Designed full system architecture including ER diagrams, UML Class and Sequence diagrams for a farmer-to-consumer direct marketplace platform. Developed a cross-platform application with a Python backend, React.js web frontend, and Flutter mobile app, enabling seamless farmer-consumer transactions. Integrated Machine Learning features for crop price prediction and personalized product recommendations, enhancing user engagement. Authored comprehensive project documentation and presented results to faculty, adhering to academic and plagiarism guidelines.
Blood Cell Identification Using Machine Learning
May 1, 2023 – August 1, 2023
Built an automated blood cell classification system using Python and OpenCV, reducing manual classification time and enabling faster diagnostic support. Achieved 92.5% detection accuracy through optimized image pre-processing, segmentation, and feature extraction techniques. Implemented end-to-end dataset preprocessing and feature extraction pipelines, improving model training efficiency and reproducibility. Collaborated with a cross-functional team to refine model performance and document technical findings for academic publication.
Everyday Excel, Part 1
Coursera
June 1, 2026 – Present
DP-600: Microsoft Fabric Analytics Engineer Associate
Microsoft
January 1, 2024 – Present
AZ-900: Microsoft Azure Fundamentals
Udemy
January 1, 2024 – Present
Azure Databricks and Apache Spark for Data Engineers
Udemy
January 1, 2024 – Present
Generative AI Fundamentals
Udemy
January 1, 2024 – Present
Agile Project Management
Unknown
January 1, 2024 – Present
Achieved a perfect score (100%) on the 'Application Developer — Azure Cloud Full Stack' test, indicating exceptional proficiency in the evaluated skills.
Strengths
Limitations
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of interests, from data analytics ETL pipelines to machine learning for medical diagnostics and a full-stack agricultural marketplace. This breadth of experience, coupled with certifications in Generative AI and Agile Project Management, suggests an adaptable individual keen on exploring various technical domains. The current role at Capgemini as a Software Engineer (Analyst) aligns well with a data-driven, cloud-focused environment. The candidate's continuous learning mindset, evidenced by multiple certifications, indicates a proactive approach to skill development, which is a positive cultural attribute. The blend of academic and professional experience, along with a focus on practical application, suggests a good fit for organizations valuing innovation and continuous improvement.
Soft Skills & Operational Fit
The candidate's resume highlights 'Team Collaboration', 'Problem-Solving', 'Critical Thinking', 'Time Management', 'Adaptability', and 'Communication' as soft skills. Project descriptions show collaboration in refining model performance and partnering cross-functionally with stakeholders. The professional summary also mentions being a 'strong communicator and collaborative team member'. These indicate a good operational fit for roles requiring teamwork and problem-solving in a dynamic environment. However, the psychometric test score (236/500) suggests potential areas for improvement in logical reasoning, work attitude, or stress handling, which could impact operational fit in high-pressure scenarios.
Achieved a perfect score (100%) on the 'Application Developer — Experience Full Stack (Python)' test, demonstrating excellent command of Python full-stack development.
Strengths
Limitations
Achieved a perfect score (100%) on the 'Application Developer — Experience Frontend (React/TypeScript)' test, indicating superior skills in frontend application development.
Strengths
Limitations