I am a Data Engineer with 4+ years of experience designing and building scalable data platforms and analytics solutions using Azure, Databricks, and Snowflake. I specialize in developing robust ETL/ELT pipelines, optimizing data warehouse models, and delivering high-quality datasets that power business decision-making and advanced analytics. 🔹 Core Expertise - End-to-end Data Pipeline Development (Batch & Streaming) - Lakehouse Architecture (Medallion: Bronze, Silver, Gold) - Data Modeling & Warehousing (Snowflake, dbt) - Distributed Processing with PySpark - Data Quality, Governance & Reliability (Unity Catalog) - CI/CD & DevOps for Data Platforms 🔹 What I Do - Build and optimize scalable pipelines using Databricks, Azure Data Factory, and PySpark - Design modular, high-performance data models in Snowflake and dbt - Process multi-terabyte datasets with a focus on performance and reliability - Implement data quality checks, monitoring, and governance frameworks - Integrate modern technologies including LLMs and LangChain into data workflows 🔹 Key Achievements - Improved pipeline performance by up to 40% through cloud migration and optimization - Reduced manual QA effort by 70% using automated data quality frameworks - Delivered platforms processing TB-scale data daily with high reliability (99.9%) - Reduced deployment time by 95% using CI/CD automation I’m passionate about building modern data platforms, solving complex data problems, and enabling organizations to scale their data capabilities efficiently.
