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Data Engineer with less than a year in ETL Pipeline Development & Big Data
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Assessing your cultural and operational fit
Data Engineer with 6 months of internship experience building and maintaining Python- and SQL-based data pipelines for transactional systems. Familiar with modern data stack tools including PySpark and Databricks. Experienced in transforming raw operational data into clean, structured datasets to support analytics dashboards and reporting workflows.
COMSATS University Islamabad
Bachelor of Science · Computer Science
September 1, 2021 – July 1, 2025
TecniForge
Data Engineer Intern
October 1, 2025 – April 1, 2026
Sahiwal, Punjab, Pakistan
E-Commerce Sales Data Warehouse
January 1, 2026 – March 1, 2026
Ingested and processed raw e-commerce sales CSV data using PySpark on Databricks Community Edition, applying transformations and loading into a structured schema. Built SQL queries on top of the processed data to generate sales, inventory, and revenue summary reports.
Weather Data Pipeline
October 1, 2025 – December 1, 2025
Built an automated ETL pipeline that fetches real-time weather data from OpenWeatherMap API, transforms it, and loads it into a PostgreSQL database for analysis. Scheduled pipeline runs using Python scripts with logging and basic data quality checks.
Python for Data Engineering
DataCamp
June 1, 2026 – Present
IBM Data Engineering Professional Certificate
Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's profile shows a clear focus on data engineering, with both personal projects and an internship aligning directly with the target role. The diversity of projects (e-commerce sales, weather data) indicates adaptability and a willingness to explore different data sources and use cases. The certifications further demonstrate a proactive approach to skill development, which aligns with a culture of continuous learning. The candidate is still early in their career, which might indicate a strong desire to learn and grow within a supportive team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work independently on end-to-end data pipeline development. The internship experience suggests an understanding of operational workflows in a professional setting, including data ingestion, transformation, and reporting. However, without psychometric or English test scores, a comprehensive assessment of soft skills, stress handling, and team collaboration is not possible.