Design, develop, and maintain scalable data pipelines using PySpark, Java, and SQL.
Build and optimize ETL/ELT workflows for banking data integration and processing.
Develop and enhance banking applications and dashboards using Angular.
Design and consume REST APIs for seamless application and data integration.
Write and optimize complex SQL queries for data extraction, transformation, and reporting.
Ensure data quality, integrity, security, and compliance across banking systems.
Integrate data from Core Banking, Payments, AML/KYC, and other financial applications.
Troubleshoot and resolve production issues related to applications and data pipelines.
Collaborate with cross-functional teams to deliver scalable banking solutions.
Participate in Agile development, code reviews, testing, and production deployments.
Requirements
- Proven experience as a Data Engineer with a focus on data integration, ETL, and big data technologies.
- Strong proficiency in Python programming.
- Ensure data quality and consistency throughout the ETL pipeline.
- Implement data integration processes to aggregate and consolidate data from various sources.
- Hands-on experience with big data technologies such as Hadoop, Spark, etc.
- Familiarity with data modelling concepts and best practices.
Sign in
To continue your applicationor continue with email
By continuing you agree to our Terms & Privacy Policy.
