Data Engineer (PySpark)

We are looking for a skilled Data Engineer to join the ** Data Engineering Chapter** supporting the Group Operations team at ENBD. The ideal candidate will be responsible for building scalable data pipelines, performing data analysis, and delivering high-quality data solutions aligned with enterprise data models.

Key Responsibilities

• Collaborate with the Group Operations Team to understand business and data requirements on a daily basis
• Perform Impact Assessment for new and existing data changes
• Conduct Technical Data Mapping and ** Data Profiling** activities
• Design, develop, and maintain ETL pipelines for data extraction, transformation, and loading
• Build data solutions to feed into AECB application as per prescribed data models
• Develop and optimize data pipelines using PySpark on modern data platforms
• Ensure data quality, consistency, and integrity across systems
• Perform unit testing, debugging, and deployment of data solutions
• Leverage modern tools and AI technologies (e.g., Claude) to enhance development efficiency and reduce operational errors
• Work closely with cross-functional teams including business analysts, architects, and QA

Required Skills & Qualifications

• Strong hands-on experience with PySpark and distributed data processing
• Experience in Informatica BDM Development (Big Data Management)
• Solid understanding of ETL/ELT concepts and data pipeline architecture
• Expertise in data mapping, data profiling, and impact analysis
• Experience working with large-scale data systems and cloud/data platforms
• Strong SQL skills and understanding of data warehousing concepts
• Familiarity with **banking/financial domain **(preferred but not mandatory)
• Knowledge of AI-assisted development tools (e.g., Claude) is a plus
• Good problem-solving and analytical skills

Nice to Have

• Experience with AECB data/reporting systems
• Exposure to big data ecosystems (Hadoop/Spark clusters)
• Understanding of data governance and compliance standards