Abhilash Amilineni

I’m an Azure Data Engineer with around 5 years of experience designing, developing, and optimizing data pipelines using Microsoft Azure technologies. I focus on turning raw data into analytics-ready datasets that teams can trust for reporting and decision-making.

I’ve built scalable ETL/ELT pipelines with Azure Data Factory, Azure Databricks (PySpark), Azure Synapse Analytics, and Azure Data Lake Storage Gen2. I implement lakehouse architecture using the Medallion model (Bronze, Silver, Gold) for large-scale structured and semi-structured data.

My work emphasizes reliable, incremental processing—through CDC frameworks, watermark-driven incremental loads, and Spark-based distributed transformations. I also improve performance with partitioning strategies, caching mechanisms, and optimization techniques like predicate pushdown.

I’ve delivered platforms across Banking, Healthcare, and Retail, including a banking risk/financial analytics platform and healthcare analytics integrations. I bring a strong quality mindset with validation checks (duplicates, null checks, schema validation) and proactive pipeline monitoring using Azure monitoring tools.