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Hussein N. AWS, Data Engineering and Serverless Platforms

My name is Hussein N. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: Python, Data Scraping, Amazon Kinesis Video Streams, Serverless Computing, AWS Lambda, etc.. I hold a degree in Master of Science in Information Technology (M.Sc.(I.T)), Bachelor of Applied Science (B.A.Sc.). Some of the notable projects I’ve worked on include: Redshift to ElasticSearch data pipeline. I am based in Dublin, Ireland. I've successfully completed 1 projects while developing at Softaims.

My expertise lies in deeply understanding and optimizing solution performance. I have a proven ability to profile systems, analyze data access methods, and implement caching strategies that dramatically reduce latency and improve responsiveness under load. I turn slow systems into high-speed performers.

I focus on writing highly efficient, clean, and well-documented code that minimizes resource consumption without sacrificing functionality. This dedication to efficiency is how I contribute measurable value to Softaims’ clients by reducing infrastructure costs and improving user satisfaction.

I approach every project with a critical eye for potential bottlenecks, proactively designing systems that are efficient from the ground up. I am committed to delivering software that sets the standard for speed and reliability.

Main technologies

  • AWS, Data Engineering and Serverless Platforms

    5 years

  • Python

    2 Years

  • Data Scraping

    2 Years

  • Amazon Kinesis Video Streams

    4 Years

Additional skills

  • Python
  • Data Scraping
  • Amazon Kinesis Video Streams
  • Serverless Computing
  • AWS Lambda
  • MicroStrategy
  • Snowflake
  • Amazon Redshift
  • Data Modeling
  • Data Engineering
  • Data Science
  • Data Analysis

Direct hire

Potentially possible

Previous Company

Amazon

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Experience Highlights

Redshift to ElasticSearch data pipeline

Serverless pipeline to load data from Redshift to ElasticSearch (Serverless framework, Python) - Remodeled the data to do minimal aggregation on ElasticSearch (SQL Redshift) - Built a lambda function that calls itself recursively to run in parallel driving full load time to 25 minutes down from 12 hours - Changed cluster spec to decrease costs by 40% but still achieved 5x speed because of the data remodeling - Process is fully idempotent and self-fixing - Automated alerts on both cluster health and data accuracy metrics

Education

  • Czech University of Life Sciences Prague

    Master of Science in Information Technology (M.Sc.(I.T)) in Computer engineering

    2014-01-01-2016-01-01

  • The American University in Cairo

    Bachelor of Applied Science (B.A.Sc.) in Computer science

    2005-01-01-2010-01-01

Languages

  • Arabic
  • English

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