• Good experience as a Data Engineer with strong expertise in designing and building scalable data pipelines and data platforms for financial institutions.• Extensive hands-on experience with ETL/ELT pipelines using Python, PySpark, and SQL, managing structured, semi-structured, and unstructured data across multiple cloud environments.• Proven expertise in real-time data ingestion using tools like Apache Kafka, AWS Kinesis, and Kafka Confluent, enabling event-driven processing for fraud detection and trading analytics.• Proficient in designing batch ingestion pipelines using Apache Spark (Scala, PySpark) and Airflow/GCP Composer, supporting large-scale financial reporting and regulatory compliance.