I’m a Senior Data Engineer with 10+ years of experience building scalable, cloud-based data pipelines and modern data platforms. I specialize in architecting serverless, event-driven ETL pipelines, optimizing big data workflows, and enabling data-driven decision-making for enterprises across service-based, consulting, and product environments. Over my career, I’ve delivered solutions for organizations like Macquarie, PayU, Levi’s, Dunnhumby, and Adani, gaining deep exposure to enterprise-scale data systems, migration projects, and real-world engineering challenges. 📌 What I Do: Architect serverless, event-driven pipelines on AWS for real-time ingestion and processing, reducing manual touchpoints by 90% and accelerating analytics readiness. Design cost-optimized ETL workflows with Apache Spark on EMR, orchestrated via Apache Airflow—fine-tuning Spark jobs to reduce cluster runtime and improve billing accuracy by 30%. Implement Glue Jobs & Workflows with schema validation, partitioning, and optimized S3/Redshift read-write operations. Optimize SQL-based ETL pipelines, data models, and OLAP systems, improving query performance and reporting efficiency. 🔧 Tech Stack: Data Processing: PySpark, Scala, Glue Cloud: AWS (S3, Lambda, EC2, Step Functions, MWAA, Redshift, EMR, Lambda) Languages: Python, SQL Workflow & Orchestration: Airflow, Step Functions 📈 Achievements & Recognition: AWS Certified Data Analytics – Specialty | AWS Solutions Architect – Associate 'Above And Beyond’ – KPMG | ‘Stellar’ – Cognizant If you’re looking for practical mentorship, career guidance, or help navigating Big Data / Data Engineering, I’d be happy to support you