Data Engineer with less than a year in SQL & Python for ETL Workflows
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Junior Data Engineer / Data Operations professional with hands-on experience in SQL, Python (Pandas), and ETL-style data workflows. Skilled in data extraction, cleaning, transformation, validation, and preparing datasets for analytics and machine learning pipelines. Familiar with relational databases and data pipeline best practices.
Dr. NGP Arts and Science College, Coimbatore
B.Sc · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2025
Prodigy Infotech
Machine Learning Intern
December 1, 2025 – May 31, 2026
India
Crime Type Prediction (Data Preparation & Pipeline Focus)
January 1, 2025 – December 31, 2025
Extracted, cleaned, and transformed 8,000+ rows of raw data for analytics and ML usage. Prepared structured datasets optimized for downstream model training. Applied data validation checks to ensure accuracy and consistency.
Disease Diagnosis Dataset Processing
January 1, 2025 – December 31, 2025
Built ETL-style preprocessing workflows for clean, analysis-ready datasets. Performed scaling and feature preparation to improve data consistency.
C
Infosys Springboard
June 1, 2026 – Present
C++
Infosys Springboard
June 1, 2026 – Present
Python
Infosys Springboard
June 1, 2026 – Present
Tableau Fundamentals
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internship show a clear interest in data-centric roles, particularly in data preparation and machine learning support. The certifications in programming languages (C, C++, Python) and Tableau indicate a proactive approach to skill development. The focus on data cleaning, transformation, and validation aligns well with the core responsibilities of a Data Engineer. However, the experience is primarily academic and entry-level, which might require significant mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate's resume indicates a focus on structured data processing and documentation, suggesting an organized approach to tasks. The academic projects and internship highlight an ability to work on defined data preparation workflows. However, there is insufficient data to assess advanced soft skills like leadership, complex problem-solving under pressure, or cross-functional collaboration.