Mohammed Nazeem

I am a dedicated Data Engineer with hands-on experience building scalable ETL and streaming pipelines using Python, Apache Spark, Kafka, and Airflow. I focus on designing reliable data workflows and architectures that support analytics and data-driven decisions.

I've implemented batch and real-time pipelines, constructed a star-schema data warehouse, and automated ETL with Python and Linux shell scripting to ensure data accuracy and reliability. I have practical experience with Hadoop, HDFS, and large-scale data processing.

In internships and junior development roles, I developed data models, reporting queries, and data quality checks using SQL, Pandas, and NoSQL systems like MongoDB and Cassandra. I also built Airflow DAGs to orchestrate and monitor workflows and created visualizations to make insights accessible.

I hold a Bachelor of Engineering in Computer Science and earned the IBM Data Engineering Professional Certificate. I bring a pragmatic, learning-oriented approach and a passion for building robust data platforms that enable teams to act on trustworthy insights.