Muhammad Fahim

Reverse-engineered and scraped complex JavaScript-heavy websites, extracting structured data from dynamic APIs. Designed and implemented scalable data ingestion pipelines to transform and persist scraped data into PostgreSQL databases.

Built a serverless ETL pipeline that triggers on CSV uploads to S3, processes data in AWS Lambda using pandas/NumPy, and loads it into Snowflake for analytics while indexing into Elasticsearch. Optimized PostgreSQL performance with table partitioning and delivered end-to-end scraping solutions.

Designed and implemented a scalable data ingestion pipeline that scraped and processed data from 30M+ websites and 11M LinkedIn company profiles. Implemented ETL pipelines with Apache Airflow and Kafka, delivered RESTful APIs with Django REST Framework, and integrated AWS services.

Engineered scalable web scrapers and crawlers by analyzing diverse website structures. Developed and deployed backend services using FastAPI, integrated with cloud infrastructure, and applied Pandas for data cleaning and transformation.

Completed the Introduction to Big Data with Spark and Hadoop course, covering big data processing frameworks.

Completed the ETL and Data Pipelines with Shell, Airflow and Kafka course, covering ETL pipeline development.

Completed the Data Engineering Foundation Specialization, covering foundational data engineering concepts.

Completed the Data Warehousing Fundamentals course, focusing on data warehousing principles.

Completed the Google Cloud Platform Fundamentals: Core Infrastructure course, covering GCP core services.

Completed the Agile Project Management course, covering agile methodologies and project management.

Pursued a Bachelor of Science in Information Technology, covering core computer science and IT subjects.