Hi, I’m a Data Engineer with 5+ years of experience working across Azure and AWS cloud data platforms, helping organizations build scalable, reliable, and high-performance data pipelines. My work focuses on transforming raw, complex datasets into analytics-ready data that empowers teams to make data-driven decisions. I specialize in designing and optimizing end-to-end ETL/ELT pipelines, ensuring data quality, performance, and cost efficiency in cloud environments. I have hands-on experience working with modern data platforms including Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Databricks, Azure SQL, AWS S3, Glue, EMR, Lambda, Redshift, and CloudWatch, along with strong expertise in Python, SQL, PySpark, and Apache Spark for distributed data processing. One unique aspect of my background is my strong foundation in ETL testing and Quality Engineering, which allows me to design highly reliable data pipelines with proper validations, monitoring, and failure handling mechanisms. What I Can Help You With • Data Engineering career guidance • Transitioning into Data Engineering from ETL / Data Analyst roles • Understanding Azure Data Engineering architecture • Learning AWS Data Engineering services • Building end-to-end ETL/ELT pipelines • Working with Apache Spark & PySpark • Writing efficient SQL for large-scale data processing • Designing scalable cloud data pipelines • Best practices for data quality, monitoring, and optimization • Interview preparation for Data Engineer roles If you're looking to grow in Data Engineering, understand cloud data platforms, or build production-grade data pipelines, I’d be happy to share insights from my experience.