Jobs → Data & Analytics → Data Engineer

About the Role We are seeking a highly skilled Big Data Engineer with strong expertise in GCP cloud technologies, PySpark, ETL development, and large-scale data processing solutions. This role focuses on designing and developing scalable data pipelines within the banking and financial compliance domains. Key Responsibilities • Design, develop, and optimize scalable big data pipelines using GCP technologies • Build and maintain ETL workflows for large-scale data transformation and analytics • Develop event-driven and streaming data solutions using Kafka or GCP PubSub • Work with structured and unstructured datasets for enterprise-level analytics and reporting • Implement scalable data processing solutions using Spark, Hadoop Hive, and DataProc • Collaborate with product, analytics, and engineering teams to deliver business-critical solutions • Improve engineering efficiency through automation, CI/CD pipelines, and modern DevOps practices • Support Financial Crimes and Anti-Money Laundering (AML) technology initiatives through data engineering solutions Requirements • Strong expertise in Big Data Engineering, Data Analytics, and ETL development • Hands-on experience with GCP services including BigQuery, Airflow, DataProc, and PubSub • Strong proficiency in Python, PySpark, SQL, and Shell Scripting • Experience building scalable event-processing pipelines using Kafka or GCP PubSub • Strong knowledge of distributed systems, relational databases, and data modeling • Experience with CI/CD pipelines, Jenkins, Git, and automated testing frameworks • Strong understanding of SDLC methodologies, Agile, and Scrum practices • Excellent analytical, troubleshooting, and problem-solving abilities