I am a Senior Data Engineer with more than five years of experience designing, building, and optimizing scalable data pipelines and cloud data platforms. I specialize in transforming large-scale enterprise data into reliable, analytics-ready datasets.
I have strong hands-on experience with Databricks, PySpark, Apache Spark, Python, SQL, Azure, Delta Lake, and Lakehouse architectures. I build ETL and ELT solutions that support reporting, analytics, AI, fraud detection, credit risk, and customer intelligence use cases.
I have improved critical pipeline performance by up to 75%, reducing delivery cycles from multiple days to less than 24 hours. I have also integrated more than 30 enterprise sources into centralized and standardized data foundations.
I am experienced in data modeling, data quality, metadata management, schema documentation, validation, traceability, and feature engineering. I focus on delivering dependable datasets that are easy for downstream teams to consume.
I work effectively with international, cross-functional teams on technical design, estimation, delivery, and production support. I also contribute to CI/CD and deployment automation using Azure DevOps, Git, YAML, Helm, and enterprise scheduling tools.
I hold Databricks Data Engineer Associate, Microsoft Fabric Data Engineer Associate, and AWS Cloud Practitioner certifications. My background combines data engineering, cloud platforms, banking systems, software development, and data-intensive enterprise environments.
