About
An aspiring and detail-oriented Data Engineer with a strong foundation in designing and implementing end-to-end ETL/ELT pipelines. Proficient in leveraging Big Data technologies like PySpark, Snowflake, and the Azure cloud suite (Data Factory, Databricks, Synapse) to process and transform large-scale datasets. Possesses hands-on experience in architecting data solutions using the Medallion architecture (Bronze, Silver, Gold) and orchestrating workflows with Apache Airflow. Eager to apply robust problem-solving skills to build scalable and efficient data systems.
Skills & Expertise (26)
Work Experience
Data Engineer
Olist E-commerce
Present - Present
Designed and implemented a complete ETL solution following the Medallion Architecture to process 1M+ e-commerce records from multiple sources (MySQL, MongoDB, JSON). Engineered ingestion pipelines in Azure Data Factory to dynamically pull raw data from various sources and land it in the Bronze layer in Azure Data Lake Storage. Leveraged Azure Databricks and PySpark to perform complex transformations, aggregations, and data enrichment, storing the cleaned, business-ready data in the Silver layer. Utilized Azure Synapse Analytics to further refine the data in the Gold layer, preparing it for consumption by analytics and visualization tools like Power BI and Tableau.
Data Engineer
Hotel Booking Analytics
Present - Present
Developed an end-to-end data warehousing and analytics solution using Snowflake to analyze hotel booking trends, implementing a Medallion Architecture for structured data processing. Engineered data pipelines within Snowflake to ingest raw booking data, performing data cleaning (handling nulls/duplicates) and standardization across Bronze and Silver layers. Utilized Snowflake-SQL to calculate critical business KPIs, including Total Revenue ($577K+), Average Booking Value ($334.11), and Total Guest counts (5,000+). Built a comprehensive Snowflake Dashboard to visualize monthly revenue trends and segment bookings by category (Deluxe, Suite, Standard) and status (Confirmed, Cancelled, No-Show) to drive data-led decision making.
Data Engineer
NASA APOD
Present - Present
Developed a containerized ETL workflow using Docker to ensure a reproducible and isolated environment for Airflow and Postgres. Orchestrated a daily data pipeline using an Airflow DAG to automatically extract the 'Astronomy Picture of the Day' from NASA's public API. Implemented transformation logic using Python within Airflow to parse the response and prepare it for structured storage. Loaded the transformed, valuable data into a PostgreSQL database, making it persistent and available for querying and analysis.
Education
Bachelor of Technology in Computer Science & Engineering - Dr. A.P.J. Abdul Kalam Technical University (ABES Institute of Technology)
2020 - 2024 · Afghanistan
Certifications
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Open to Relocation
Skills (26)
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