Data Engineer + Python

- Build and optimize data pipelines for AML monitoring and regulatory reporting - Design and implement ETL/ELT processes using Python & Oracle - Work on data ingestion, transformation, validation, and quality checks - Collaborate with global teams across CIB, Compliance, and Data Hub - Drive automation, testing, and DevOps practices in data workflows - Contribute to scalable and high-performance data architecture

- Strong experience in Python (data engineering use cases) - Expertise in SQL & Oracle PL/SQL - Hands-on experience in ETL pipeline development - Good understanding of data analysis & data mapping - Experience in Data Warehousing concepts (OLTP/OLAP, schema design) - Exposure to AML / Banking / Financial domain (highly preferred) Nice to Have: - Experience with PySpark / Spark / Scala - Knowledge of Airflow / ADF / Prefect - Exposure to Kafka / streaming pipelines - Familiarity with Cloud (OCI / AWS / Azure) - Understanding of data governance, lineage & regulatory frameworks If you have 5 to 7 years of experience in Data Engineering, possess strong problem-solving skills with an ownership mindset, can work effectively with global stakeholders, and thrive in quick-paced, data-driven environments, this role is tailored for you. By joining us, you will have the opportunity to work with a leading global bank operating in 65+ countries, be part of cutting-edge AML & regulatory data initiatives, gain exposure to large-scale enterprise data platforms, and experience a collaborative and diverse international work culture.