I’m a results-driven Data Engineer with 4+ years of experience building and optimizing cloud-native data pipelines across Azure and AWS environments. My expertise lies in designing scalable, high-performance ETL workflows using tools like Databricks, Azure Data Factory (ADF), and Apache Spark, while leveraging storage solutions such as ADLS Gen2, AWS S3, and enterprise data lakes. I specialize in: • Developing cloud-first data pipelines for ingestion, transformation, and analytics • Implementing data engineering best practices, including modular design, automation, and CI/CD • Building robust staging layers, curated datasets, and optimized views for downstream analytics • Cross-cloud integration strategies and cost-efficient architecture design With a strong foundation in Python, SQL, and distributed systems, I take pride in delivering clean, accurate, and insight-ready data to empower data science, BI, and business teams. 🔎 Actively seeking challenging opportunities in data engineering, cloud architecture, or platform development to continue growing and solving impactful data problems.