Khalid Oujnine

Assignment within the finance department, with an international scope. Objective: to ensure the reliability, structure, and exposure of financial data for budget monitoring, performance tracking, and overall management. Environment based on GCP, Oracle, and Adeo's internal tools. Ingestion and consolidation of Oracle data and internal flows into BigQuery via Cloud Storage and internal pipelines. Functional analysis with finance teams to translate needs into business rules and analytical models. Data modeling in BigQuery to consolidate expenses, forecasts, and commitments. Python development for data cleaning, validation, and preparation. Construction and optimization of workflows in Cloud Composer to automate updates. Technical and functional documentation on queries, business rules, and models. Creation of Looker and PowerBI reports to analyze variances and trends. BigQuery optimization through partitioning and performance improvements. Use of Terraform to structure cloud architecture and deploy GCP components. Support via Jira and ServiceNow with incident analysis. Collaboration with several international teams on financial and technical topics. Work in an agile organization with sprint tracking and continuous prioritization with business stakeholders.

Fraud detection project at the point of sale. Implementation of a real-time system to analyze transactions, detect anomalies, and alert teams. Construction of indicators to monitor risks and reduce losses. Collection and ingestion of point-of-sale data. Design of real-time pipelines with Pub Sub and Dataflow. Data modeling in BigQuery with dedicated tables, views, and schemas. Development of dbt models to clean, enrich, and structure data. Addition of dbt tests to ensure quality. Documentation and governance via dbt. Definition of analysis rules and detection algorithms integrated into BigQuery and dbt. Creation of a real-time alert engine via Redis, Memorystore, and Kafka. Implementation of KPIs to track fraud, estimated losses, and anomalies per store. Development of dashboards in Looker. Orchestration of workflows with Cloud Composer to automate recalculations. Implementation of CI/CD GitLab for deployments. Collaboration with security, finance, and operations teams. Optimization of BigQuery performance with partitioning, clustering, and cost reduction.

Daily Banking and Payments Project. Objective: ensure data consistency, improve the readability of functional models, and enhance the availability of datasets for analytical uses. Analysis of T24 structures to understand tables related to operations, accounts, and payments. SQL checks on Oracle to identify discrepancies, duplicates, and inconsistencies. Redesign and optimization of SQL queries used by analysts, reducing execution times. Creation of consolidated datasets in Oracle to feed BI processes, including PowerBI. Contribution to business rules with Retail Banking teams to clarify calculations and granularity levels. Documentation of flows, queries, and models to facilitate operations. Support for analysts and operational teams for ad-hoc needs and anomaly resolution. Improvement of pipelines with the Data Engineering team to ensure data availability. Daily collaboration with IT, Data, and Business teams in a secure and regulated environment.