Omar Ghannam

Within the Data Factory, integrated into the Corporate Finance Feature Team dedicated to Group Finance's analytical steering.

Performance Management (Group Finance)

• Definition and structuring of financial KPIs (P&L, corporate indicators)

• Design and evolution of Power BI dashboards dedicated to performance steering

• Provision of datasets for BI and self-service analytics uses

• Support for Finance teams in exploiting indicators and decision-making tools

Data Transformation & Modeling (GCP)

• Development of data transformations using dbt / SQL on BigQuery

• Modeling of Finance data marts for reporting and decision-making analysis

• Contribution to a shared Finance data foundation

• Optimization of processing performance and analytical models

Data Quality & Reliability

• Data quality control and deliverable validation

• Pipeline monitoring and anomaly correction

• Documentation of data models and transformations

Environment: Power BI, BigQuery, dbt, SQL, DAX, Jira, Confluence, Agile Scrum

In the data collection Squad of the IT department's Big Data project, I was the Data Product Owner responsible for scoping and analyzing business needs with the objective of providing data specific to business objects such as: the catalog of cash registers, stores, and products, sales data, discounts and benefits, store purchases and inventory, and regional purchasing centers. My responsibilities included:

▪ Defining technical and functional specifications for collecting, qualifying, and consolidating data, and then monitoring them as needed.

▪ Estimating necessary developments in collaboration with data engineers.

▪ Testing and validating deliverables to ensure alignment with business needs.

▪ Supervising production to detect anomalies and guarantee data integrity.

▪ Qualifying and continuously improving collected data to ensure its accuracy and relevance.

Environment & Tools: Google Cloud Platform (Cloud Run, Storage, BigQuery), DBT, Airflow, Azure DevOps, Jira, and Confluence, Agile Scrum Methodology.

For the Marketing department of the fresh produce market, I held the dual role of decision support project manager and Data Analyst with the objective of optimizing data quality and processing.

▪ Defining technical and functional specifications for collecting, qualifying, and consolidating data, and then monitoring them as needed.

▪ Prioritizing and planning tool evolution or migration requests.

▪ Monitoring and coordinating developments with IT teams.

▪ Assisting and supporting business users: conducting workshops, creating dashboard mockups and dashboards on Power BI.

▪ Controlling the quality of deliverables at each project milestone and acceptance.

Environment & Tools: Server (MS-SQL DB, SSIS), Jira, Confluence, Cloud Azure, Data Factory, Azure Synapse Analytics, Power BI, Azure DevOps, Agile Methodology.