I am a Data Engineer specializing in real-time, large-scale data pipeline architecture and high-throughput data systems that enable data-centric insights. Leveraging skills in Python, SQL, PySpark, and Big Data frameworks (including Hadoop, Spark, Kafka), I design and implement robust solutions to transform structured, semi-structured, and unstructured data into actionable insights.𝐊𝐞𝐲 𝐒𝐭𝐫𝐞𝐧𝐠𝐭𝐡𝐬:▪️ Real-Time Data Pipeline Design: Expert in end-to-end pipeline creation to support data extraction, transformation, enrichment, and loading across diverse data sources.▪️ Scalable Data Infrastructure: Proven experience in building scalable infrastructure for data warehousing, relational databases, in-memory caching, and searchable document databases.▪️ Process Optimization: Skilled in identifying and executing process improvements to optimize data delivery, scalability, and reliability, ensuring high performance and efficiency.▪️ Advanced Data Modeling: In-depth knowledge of data warehousing and data modeling with the ability to design conceptual data flows that support business objectives.▪️ Data Integration & Lakes: Skilled in data lake management using AWS cloud services, enabling scalable and flexible data processing across datasets.My expertise in cloud data engineering (particularly with AWS), combined with advanced skills in Unix, Bash, Git, Cassandra, PostgreSQL, and Apache Airflow, allows me to build high-performance systems tailored to business needs. I love working with new data technologies to find fast and helpful insights that have a positive impact.I enjoy helping the community 🌱, sharing knowledge 💡, and making an impact 🔨. Let’s connect to explore collaboration or insights