Nizar Ben Debba

Context: Within a team of 7 people working in SCRUM mode, the mission's goal is to calculate and explain the bank's P&L based on various data sources from pricers Baccardi, Riskone, and Highway. This is all done in a Big Data and Azure environment.

Mission:

• Integration of I2R notifications into the cube

• Implementation of a pipeline composed of Spark jobs and APIs

• Design and development of code for notification processing

• Design and implementation of new metrics for income attribution

• Design and development of APIs

• Deployment of APIs in AKS

• Building Docker images in Harbor

• Externalization of configurations and implementation of Spring Cloud Config

• Design and implementation of a Spark job to write files to the lake

• Scheduling of Spark jobs

• Migration of APIs to new AKS clusters

• Kubernetes migration

• Code Review

• Release and Support

Technical Environment: Java 8, Spring, Spring Boot, Spring Cloud, Lombok, Git, Maven, Gradle, PostGreSQL, Junit 4, EasyMock, PowerMock, Mockito, LogBack, Cucumber, Swagger, Curl, Elasticsearch, Logstash, Kibana, Jenkins, Sonar, Grafana, Azure portal, Kubernetes, HDInsight, Azure services, Key Vaults, Storage accounts, Private DNS, EventHubs, HelmChart, yaml, Azure PostgreSQL, Harbor, Kerberos, Keepass, Groovy, Spark, Hive, HBase, Yarn, Oozie, Ambari, Zepplin, XlDeploy, Puppet, Shell, ActivePivot

Context: Within a team of 5 people working in SCRUM mode, the project's goal is to improve the performance of the 'Calypso' trading and risk software for BNP CIB's needs by implementing technical solutions to handle the increasing data volume.

Mission:

• Design and development of new features

• Installation and configuration of Elasticsearch and Kibana

• Creation of Kibana dashboards and performance monitoring tools

• Installation and configuration of an Elasticsearch backup server

• Java implementation of mass data sending to Elasticsearch in a multi-threaded context

• Improvement of Java code and SQL query performance

• Code Review

• Creation of Jenkins jobs

• Release and Support

Technical Environment: Java 8/6, Spring, Swing, Jboss, SVN, Maven, Oracle 10g, Junit 4, EasyMock, PowerMock, Mockito, JMS, RMI, Elasticsearch, Logstash, Kibana, Jenkins, Sonar, Shell, Gradle, Curl

Context: Within a team of 7 people working in SCRUM mode, the project's goal is to centralize market data from various sources into a Data Lake to efficiently generate numerous KPIs, monitor the performance of the entire value chain from Front Office to Accounting in terms of risks, deadlines, quality, and performance, and effectively respond to regulatory requests. The ability to monitor our production daily (data quality) is also a key aspect.

Mission:

• Needs analysis and choice of the Big Data solution to implement

• Technical architecture design

• Setup of Hadoop, Sqoop, Spark, and Hive

• Project creation and technical foundation setup

• Implementation of various parsers for large files based on sources

• Multithreading management

• Data storage in HDFS and Hive

• Static data storage in Elasticsearch

• Development of REST Web Services

• Implementation of data encryption and filtering

• Performance improvement

• Participation in technical interviews for candidate validation

• Candidate Kata evaluation

Technical Environment: Java 8, Git, Maven, Hadoop, Sqoop, Spark, Hive, Oozie, Spring Security, Spring Test, Jasypt, Windows, Linux, Elasticsearch, Hue, Jenkins, Hortonworks, Lombok, Kibana, Swagger, Logstash