Data Engineer
Motivated and skilled Data Engineer with a strong foundation in data analytics, backend development, and cloud computing. Proficient in designing, building, and optimizing data pipelines, scalable ETL proc…
Data Engineer
Motivated and skilled Data Engineer with a strong foundation in data analytics, backend development, and cloud computing. Proficient in designing, building, and optimizing data pipelines, scalable ETL processes, and robust data storage solutions. Experienced in Python, SQL, and cloud technologies such as AWS and Databricks, with hands-on expertise in developing and deploying data-driven applications and models.
Educational Background:
Pursuing B.Tech in Computer Science and Engineering (2025), complemented by a Diploma in Electrical Engineering.
Certified in DBMS & MySQL, Python, Machine Learning, Power BI, and AWS Cloud Practitioner (in progress).
Technical Proficiency:
Programming: Python, JavaScript, SQL, Java.
Databases: MySQL, SQL.
Tools: Power BI, Excel, Git/GitHub, CI/CD pipelines.
Cloud Computing: Databricks, AWS (cloud architecture and deployment).
Data Engineering: Data pipeline creation, data cleaning, data processing optimization, and model deployment.
Professional Experience:
Internship in Data Analytics and Data Science: Optimized data processing workflows and enhanced machine learning models for predictive insights.
Practical contributions to data-driven decision-making through visualization and automation.
Developed and maintained scalable backend systems and REST APIs for data operations.
Projects:
Built a predictive model using linear regression for accurate forecasting.
Created an interactive quiz application showcasing API integrations.
Designed and deployed a professional portfolio website.
Career Objective:
To leverage expertise in data engineering, cloud computing, and analytics to enable data-driven decision-making and contribute to the development of scalable systems and efficient data architectures.
Applied supervised and unsupervised learning techniques to analysis and extract insights from complex datasets.
Optimized machine learning models, achieving a 15% improvement in prediction accuracy.
Used Python, Pandas, and NumPy for data wrangling and exploratory data analysis.
Developed Python algorithms that reduced data processing time by 20%, improving data mining efficiency.
Collaborated with cross-functional teams to ensure data consistency, contributing to accurate business forecasts.
Created visualizations using Power BI and Matplotlib, enhancing report clarity by 30% for decision-making.
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