A Bigdata Hadoop Engineer specializing in big data and cloud technologies, responsible for designing and implementing regulatory reporting models within a banking environment. This role focuses on developing scalable data processing solutions using Apache Spark with Scala, deployed on AWS infrastructure.
Key responsibilities include building and optimizing data pipelines, transforming large volumes of financial data to meet regulatory requirements, and ensuring data accuracy, traceability, and compliance. The engineer collaborates closely with risk, finance, and compliance teams to translate complex regulatory rules into robust, production-grade data models.
The role also involves leveraging AWS services such as S3, EMR/Glue, and Lambda to deliver efficient, secure, and cost-effective data solutions, while adhering to strict governance and audit standards. Strong emphasis is placed on performance tuning, code quality, and maintaining high availability of critical reporting systems.
Skills:
AWS knowledge
Big Data Hadoop - Hive and Spark/Scala solid experience
SQL advance knowledge - Been able to test changes and issues properly, replicating the code functionality into SQL
Worked with Code Repositories as GIT, Maven, ...
DevOps Knowledge (Jenkins, Scripts, ...) - Tools used for deploying software into environments, use of Jira.
Analyst Skills - Being able to translate technical requirements to non-technical partners and to deliver clear solutions. Been able to
create test cases scenarios.
Control-m solid experience - Been able to create jobs, modify parameters
Documentation - Experience of carrying out data and process analysis to create specifications documents
Finance Knowledge - Have a experience working in Financial Services / Banking organization with an understanding of Financial
Services / Retail, Business and Corporate Banking
Unix / Linux
A working knowledge and understanding of GenAI tools (specify tools used within your teams)