Mouhamadou Al Moustapha DIOP

– Led data architecture improvement and pipeline development for high-impact banking use cases (Remote Banking, Regulatory Reporting, Bank Reconciliation). – Drove platform modernization through robust and performant data modeling, code refactoring, unit testing, layers optimization – Designed and established cross-functional foundations for Data Observability, Data Quality et reliability, and DataOps practices. – Designed and implemented the scalable data models, optimized for high performance, storage efficiency and behavioural analysis. – Successfully delivered critical data processing jobs and KPIs.. – Acted as a technical leader by guiding the adoption of best methodologies, upskilling team members through training Favored knowledge sharing by estabilishing and animating Tech Talks and promoting engineering advanced and best practices – Effectively collaborated with stakeholders to transform complex business requirements into robust, maintainable technical solutions.

– Delivering intensive hands-on training in Spark with Scala to beginner and junior-level professionals. – Course focused on Hadoop, Spark (Scala), and Cloudera with real-world case studies – Supporting participants in data ingestion, transformation, and optimization – Troubleshooting and resolving production issues – Introduction of best practices in data ingestion, transformation, and pipeline optimization – Supporting participants in solving real-world cases inspired by the professional world

– Training on Apache NiFi, Apache Kafka, Kafka Streams & Kafka Connect for Atos Morocco with It-Gov Consulting – Design of training materials on Apache Spark Streaming, Structured Streaming, Kafka, Kafka Connect, Kafka Streams for ADN (Académie Du Numérique) France with Databeez – Training Facilitation on Apache Spark Streaming and Structured Streaming for Atos Senegal with Databeez – Delivering Big Data training sessions on Apache Spark Structured Streaming for Eviden/Atos France with Databeez

– Integration of new flows into the ingestion job. – Development and deployment of batch data processing jobs using Spark Scala for various subsidiaries of the BNP Paribas Group. – Enrichment and integration of new data into the 360° Customer Vision Project. – Production monitoring, incident troubleshooting, and problem resolution. – Exposure of data to business lines (finance, risk and compliance, etc.).

– Optimized data ingestion pipelines and added data quality / validity control – Developed Batch Data Ingestion Workflows with Hive, Shell, and Oozie – Development of real-time data processing jobs with Kafka and Spark Streaming – Developing and deploying batch data processing jobs with Spark Scala and PySpark (Python) – Automated development of Oozie workflows for data ingestion – Automated Ingestion (validity, completeness) checks using Shell scripts – Development of use cases with Spark, Hive and HBase for the 360° customer data product. – Creating exposition layers for the business and data scientists – Data Governance: Reliability, Security and Anonymization of Data

– Designed streaming jobs with Spark Streaming (Scala and Python) and batch jobs using Shell + HQL for data integration – Implementation of Unit Tests and Quality with SonarQube – Integration and Continuous Deployment of Applications in the Cluster with Jenkins – Writing documentation for the scheduling and planning team with VTOM

– Analysis and collection of needs – Designed the entire Relational Database – Developed REST APIs for the backend – Added logging and Event monitoring using Aspect Oriented Programming – Migration of data from the registration platform into the tracking platform

– Implementation and industrialization of pipelines for the ingestion of data flows – Partially automate the process of creating pipelines – Data governance and supervision of data transit – Improvement of the functional bricks of the Datalake architecture

– Develop and deploy data ingestion flows – Automating Flow Metadata Creation with Talend Jobs – Development of Kamanja containers for dimension tables and advanced data enrichments – Data Extraction Job Development – Data archiving with File Ops – Compressing and subdividing data archives with Minitar – Task Scheduling – Unit and Integration Testing (SIT) of deployed data ingestion streams

– Requirement's analysis and assessment – Designed the Database and Data modeling – Designed workflows and developed commission calculation jobs using Talend ESB – Implemented Front-End feature using Angular – Data Migration/Integration (MySQL – MSSQL) – Exposed jobs as Talend web services using Apache Karaf and OSGI bundles – Mentored team members on Talend – Unit Testing of Jobs

– Needs study and analysis, Database design – Designed mockups of user interfaces – Front-End feature development – Project Management (Scrum Master)

– Realization of a distributed storage system for data integration – Benchmarking and Choice of ETL tools, Datamarts, BI Self-service – Design of data marts based on Hadoop – Implementation of an interactive reporting tool – Integration of an acceleration engine into the solution