Data Engineer with less than a year in ETL & Machine Learning
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Assessing your cultural and operational fit
Entry-level Data Engineer with hands-on experience in ETL processes and data warehousing. Completed internship at tech startup, optimizing database queries resulting in 25% improved performance. Skilled in AWS, Hadoop, and machine learning, ready to contribute to data-driven decision-making.
Sunbeam Institute of Technology
PG-DBDA · Data Business Analytics
N/A – February 1, 2026
GH Raisoni Institute of Engineering and Technology
Bachelor of Technology · Data Science
N/A – June 1, 2024
PriMine Software Pvt. Ltd.
Data Science Intern
December 1, 2023 – June 1, 2024
Nagpur, Maharashtra, India
Job-Intelligence-System
June 24, 2026 – Present
Designed and deployed a job intelligence platform using ML, regression models, LLMs, and RAG architecture for intelligent job insights. Built a salary prediction pipeline (83% accuracy) using structured user features and Gemini-extracted job data. Developed a RAG-based chatbot with ChromaDB and Gemini API and a geospatial visualization system to enable semantic job search and map the top 50 relevant opportunities.
View ProjectUber Ride Fare Prediction
June 24, 2026 – Present
Built a distributed PySpark MLlib pipeline for Uber fare prediction using HDFS, SparkML, and automated ETL processes. Engineered custom features and trained regularized regression models, achieving 92% prediction accuracy. Conducted EDA and visualized pricing trends using Streamlit and Plotly to analyze surge pricing and service performance.
View ProjectInnovathon
Unknown
June 1, 2026 – Present
Data visualization with PowerBI
Unknown
June 1, 2026 – Present
Conference paper certificate
Unknown
June 1, 2026 – Present
Google Analytics for Beginners
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate initiative and a proactive approach to learning and applying new technologies (e.g., LLMs, RAG). The diversity of projects (job intelligence, ride fare prediction) shows a broad interest in data applications. The internship experience, while short, indicates an ability to work within a team structure. The candidate appears to be a motivated individual eager to contribute to data-driven environments.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to work on complex, multi-faceted problems. The internship experience indicates a collaborative approach and an understanding of translating business requirements into technical solutions. The focus on data-driven decision-making aligns well with operational needs in a data engineering role.