Hi everyone! I’m a Data Engineering Lead with 7+ years of experience in software engineering, including 5+ years specializing in Data Engineering and 2 years in Full Stack Development and DevOps. I specialize in designing and building scalable, cloud-native data platforms that support analytics, reporting, and AI-driven applications. My background across backend engineering, cloud infrastructure, and DevOps enables me to deliver end-to-end data solutions—from data ingestion and transformation to orchestration, deployment, monitoring, and optimization. Core Expertise: • Data Engineering: Python, SQL, Apache Spark, ETL/ELT, Data Modeling • Cloud: AWS (S3, Glue, Redshift, Lambda, IAM) • Data Platforms: Delta Lake, Apache Iceberg, Trino, Hive Metastore, Nessie • Orchestration & Automation: Apache Airflow, CI/CD, GitHub Actions • DevOps: Docker, Kubernetes, Linux, Infrastructure Automation • Backend Development: REST APIs, System Design, Microservices Key Achievements: • Led the design and development of scalable data pipelines processing large-scale datasets. • Built automated ETL/ELT workflows with monitoring, logging, and data quality validation. • Designed cloud-based data platforms using modern lakehouse architectures. • Improved deployment reliability through CI/CD automation and DevOps best practices. • Collaborated with cross-functional teams to deliver production-ready data solutions. Currently Focusing On: • Data Platform Engineering • Lakehouse Architecture (Iceberg, Delta Lake) • Real-Time Data Processing • AI & Data Engineering • Cloud-Native Data Solutions I’m open to Senior Data Engineer, Lead Data Engineer, Data Platform Engineer, and Data Engineering Manager opportunities where I can build scalable, high-performance data platforms and lead engineering initiatives.