I am a Data Engineer with a strong academic background and hands-on expertise in batch, streaming, and event-driven data pipelines. I specialize in data transformation using Python, building robust data models, monitoring pipelines, and ensuring data quality, from ingestion to visualization. I have hands-on experience with AWS Glue (PySpark), Airflow, Snowflake, Pandas, and S3-based data lakes, delivering scalable solutions that improve business decisions.
Collaborative by nature, I work closely with stakeholders to translate requirements into reliable data infrastructure. My track record includes reducing processing times, improving throughput, and maintaining high uptime through testing and automation. I’m passionate about clean code, documentation, and mentoring teammates to raise our data capabilities.
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