Nassereddine BELGHITH

cloud operations engineer

Carrefour•  June 2021 - Present

As a Cloud Operations Engineer on the Phenix Core Operations Team, my main responsibility is to ensure uninterrupted cloud computing services. This involves monitoring the performance of various cloud computing services and analyzing and resolving any issues that arise. I also perform various maintenance tasks such as backup, restoration, job scheduling, and system patching to ensure optimal functionality of cloud computing components. In addition, I specialize in migrating on-premise solutions to the cloud. To effectively monitor different jobs and applications, such as Spark jobs, K8s apps, and Kafka, I utilize various tools such as Prometheus, Grafana, InfluxDb, Stackdriver, Big Query, Rundeck, and Azkaban. I automate alerting using various methods such as email, care, incidents, and chatbot. I also monitor APIs and compute long-running/failing Spark jobs using Azkaban and Yarn APIs, with the ability to kill/run jobs/flows using Java 11. For monitoring BigQuery tables and views content, I utilize Python 3.8, BigQuery Client API, GCS, K8s Kustomize, and GCR. I also handle data ingestion via lambda functions such as Pub/Sub topics, Pub/Sub subscriptions, storage notifications, and GC logging alerts. Lastly, I led the migration of Carrefour photo solution to the cloud, which involved migrating IIS, SQL server, Elastic Search V7, DollarU, GCE, Rest API, and web serviceAs a Cloud Operations Engineer on the Phenix Core Operations Team, my main responsibility is to ensure uninterrupted cloud computing services. This involves monitoring the performance of various cloud computing services and analyzing and resolving any issues that arise. I also perform various maintenance tasks such as backup, restoration, job scheduling, and system patching to ensure optimal functionality of cloud computing components. In addition, I specialize in migrating on-premise solutions to the cloud. To effectively monitor different jobs and applications, such as Spark jobs, K8s apps, and Kafka, I utilize various tools such as Prometheus, Grafana, InfluxDb, Stackdriver, Big Query, Rundeck, and Azkaban. I automate alerting using various methods such as email, care, incidents, and chatbot. I also monitor APIs and compute long-running/failing Spark jobs using Azkaban and Yarn APIs, with the ability to kill/run jobs/flows using Java 11. For monitoring BigQuery tables and views content, I utilize Python 3.8, BigQuery Client API, GCS, K8s Kustomize, and GCR. I also handle data ingestion via lambda functions such as Pub/Sub topics, Pub/Sub subscriptions, storage notifications, and GC logging alerts. Lastly, I led the migration of Carrefour photo solution to the cloud, which involved migrating IIS, SQL server, Elastic Search V7, DollarU, GCE, Rest API, and web service Skills: Kubernetes · Elastic Stack (ELK) · Nginx · Cicd · DevOps · Google Cloud Platform (GCP) · Cloud func · Jenkins · Anglais

Software Engineer

audenseil•  January 2018 - June 2021

As a Machine Learning & data Engineer, my primary responsibility is to implement big data platforms, utilizing technologies such as Hadoop, Hive, Spark, and Google Cloud Platform, and to solve clients' problems through machine learning engineering. I use Python, Java, and Scala as my primary programming languages. I have worked on various use cases such as churn prediction, client segmentation and clustering, recommendation systems, KPIs calculation in the energy and telecom sectors, KQIs calculation for telecom user experience, and data storage optimization. Additionally, I have experience with ML model deployment on GCP. Furthermore, I have developed a machine learning library in Scala that contains the most useful supervised and unsupervised algorithms. It is compiled in the JVM and takes scalability issues into consideration, allowing for more efficient and effective implementation of machine learning solutions.As a Machine Learning & data Engineer, my primary responsibility is to implement big data platforms, utilizing technologies such as Hadoop, Hive, Spark, and Google Cloud Platform, and to solve clients' problems through machine learning engineering. I use Python, Java, and Scala as my primary programming languages. I have worked on various use cases such as churn prediction, client segmentation and clustering, recommendation systems, KPIs calculation in the energy and telecom sectors, KQIs calculation for telecom user experience, and data storage optimization. Additionally, I have experience with ML model deployment on GCP. Furthermore, I have developed a machine learning library in Scala that contains the most useful supervised and unsupervised algorithms. It is compiled in the JVM and takes scalability issues into consideration, allowing for more efficient and effective implementation of machine learning solutions. Skills: Kubernetes · Hive · HBase · Anglais · Big data · Machine Learning · Hadoop

Senior Software Engineer

Believe Digital•  February 2021 - May 2021

As a Data Engineer, my primary responsibility is to integrate various data sources (Spotify API, VK API, Itunes API, Amazon music API, etc.) while respecting the Bronze-Silver-Gold rule. I use Spark-DataBricks and Scala, referring to documentation to perform data mapping from various sources. To ensure the quality of the data, I perform data structuring using Spark and AWS DeltaLake, which includes table versioning, schema forcing, and other ACID mode operations. I also review the code, conduct unit tests, and performance tests for solutions to ensure optimal performance. Furthermore, I deploy the artifacts following a batch architecture utilizing AWS Lambda functions, AWS Databricks, and DeltaLake. In terms of technical environment, I use Spark 3.0.1, Scala 2.12, and Python 3.8 with GitLab as my source code management tool. I utilize AWS services such as S3, EMR (for jars test), Lambda function, DataBricks, and DeltaLake for data integration and management. Finally, I follow the Agile methodology to ensure the efficient and effective delivery of solutions.As a Data Engineer, my primary responsibility is to integrate various data sources (Spotify API, VK API, Itunes API, Amazon music API, etc.) while respecting the Bronze-Silver-Gold rule. I use Spark-DataBricks and Scala, referring to documentation to perform data mapping from various sources. To ensure the quality of the data, I perform data structuring using Spark and AWS DeltaLake, which includes table versioning, schema forcing, and other ACID mode operations. I also review the code, conduct unit tests, and performance tests for solutions to ensure optimal performance. Furthermore, I deploy the artifacts following a batch architecture utilizing AWS Lambda functions, AWS Databricks, and DeltaLake. In terms of technical environment, I use Spark 3.0.1, Scala 2.12, and Python 3.8 with GitLab as my source code management tool. I utilize AWS services such as S3, EMR (for jars test), Lambda function, DataBricks, and DeltaLake for data integration and management. Finally, I follow the Agile methodology to ensure the efficient and effective delivery of solutions. Skills: Spark · Aws · Azure Databricks · Test unitaire · Big data · Scala