Data Engineer Machine Learning

Qadeer Moinuddin Mohammed

Dallas Texas ***********************@*****.*** +1-972-***-****

www.linkedin.com/in/qadeer-mohammed-797033248

Summary

Results-driven Data Engineer with 1+ years of experience building scalable data pipelines, ETL workflows, and cloud-native solutions. Proficient in Python, SQL, Apache Spark, Databricks, Airflow, and hands-on across GCP, AWS, and Azure. Skilled in automating workflows, optimizing architectures, and integrating diverse data sources to support analytics and ML.

Skills

• Big Data,Machine Learning,ETL/ELT,Clustering,Deep Learning,Forecasting,Airflow

• Python,SQL,Pyspark,SQL,PostgreSQL,Azure,Databricks,Google Cloud Platform,Hadoop Education

University Of The Cumberlands, Master’s in Data Science Aug 2023 – Dec 2024

– GPA: 4.0/4.0

– Coursework: Big Data, Deep Learning, Machine Learning, Programming with Python etc. Experience

Data Engineer, Gamestop – India June 2022 – Jun 2023

– Designed and automated ETL pipelines to streamline daily data ingestion from retail systems, reducing manual intervention and improving data freshness.

– Spearheaded migration to Tableau Cloud, cutting report load times by 40% and reducing infrastructure maintenance costs by approximately $25K annually.

– Built and maintained real-time analytics dashboards to monitor store operations and inventory, enabling faster decision-making for business teams.

– Integrated and normalized data from on-premise databases and cloud sources (AWS/GCP) to improve reporting reliability and support business analytics. Projects

Handwritten Digit Recognition using Hopfield Networks,University Of The Cumberlands -Williamsburg KY

Aug 2024 - Dec 2024

– Developed an AI model to recognize handwritten digits from the MNIST database.

– Implemented Hebbian and Storkey learning rules for optimized training.

– Conducted statistical evaluations to measure model performance and accuracy. Tech Industry Salary Distribution Analysis, University Of The Cumberlands

-Williamsburg KY

Jan 2024- May 2024

– Analyzed salary trends based on experience level, company size, and remote work ratio using a dataset of 8,805 entries.

– Applied data preprocessing techniques (normalization, cleaning) to ensure data accuracy.

– Provided insights for salary negotiations and compensation strategies through Power BI visualizations .

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