Nadir Nadjem

I supported the migration of a DataOps platform to AWS as a Cloud Architect AWS / DevOps Expert. I designed and industrialized the EKS architecture, automated provisioning with Terraform, and implemented security standards (IAM, IRSA, KMS, Kyverno, OPA). I led observability, FinOps, and CI/CD initiatives, while ensuring the operational maintenance of critical Kubernetes clusters. I also developed automation solutions for Data Science teams and facilitated discussions with security, network, and infrastructure teams to ensure alignment between technical challenges and business needs.

As a Technical Architect specializing in Cloud and Data, I play a key role in designing and optimizing data pipelines as well as implementing cloud solutions. I use technologies such as Apache Spark, Apache Kafka, Hadoop, Kubernetes, and languages like Java and Python to ensure system performance and security. Key Achievements: Data Pipeline Design and Development: Creation of data pipelines for the banking fraud detection system (Spark, Kafka, Hadoop, Flink). Optimization of Spark job performance. Development of data anonymization pipelines. Development of Kafka Connect Connectors and Plugins: Design of custom connectors for IBM MQ and InfluxDB. Development of plugins for Hvault password management and data extraction. Crash Monitoring and Prediction System: Development of a monitoring system for Big Data infrastructure logs and metrics. Use of Spark, Kafka, Hive, Tensorflow for anomaly detection and crash prediction. Implementation of Big Data Services on the Cloud: Deployment of Big Data services on the IBM private cloud with Kubernetes and OpenShift. Development of Kubernetes operators and CI/CD pipelines for infrastructure management. Securing the Kubernetes Environment: Implementation of Docker image scanning pipelines. Implementation of security policies and SAML authentication. Development of secure architecture patterns for data projects.

As a Data Engineer / Devops, I designed, developed, and optimized robust and scalable Big Data solutions using Apache Spark, Apache Kafka, and Hadoop.

- N3 Support Spark, CDH, Kafka: Provide level 3 technical support for applications using Apache Spark and Kafka. Analyze and optimize Spark job performance. Perform code reviews and suggest improvements. Diagnose and resolve complex issues for users and business teams. Project: Migrating Data from HBase to Hive with Apache Spark:

- Design and execution of a data migration project from HBase to Hive. Analysis of existing data schemas and query models. Development of data transformation pipelines with Apache Spark. Implementation of validation mechanisms to ensure the integrity of migrated data. Application of Spark-specific optimization techniques. Writing detailed reports on the migration process and implemented solutions. Project: Implementing Solutions on Kubernetes and Docker Environments:

- Deployment of data processing solutions on Kubernetes clusters. Implementation of CI/CD pipelines to automate deployment and testing. Monitoring and management of application performance with Prometheus and Grafana.