Saad Bennis

Within Data-Platform at BIL, Data Engineer for integrating data from the Core Banking System (Temenos T24). Responsible for several data projects:

1. Business Data Layers (BDL) – Daily Banking, Payments, Client Fees

Development and maintenance of data pipelines covering accounts, transactions, payments, and fees.

Responsibilities:

● Design and industrialize pipelines using internal frameworks

● Implement TWS job streams and monitor daily processes

● Maintain and evolve data products

● Implement data quality controls to ensure consistency

2. FCRM (Financial Crime Risk Management) Project:

Pipelines dedicated to fraud detection and risk management using the Fiserv solution.

● Development of data pipelines to generate files required by Fiserv (transactions, end-of-day balances, clients, accounts, relationships)

● Management of production deployment, scheduling, and industrialization

● Implementation of TWS workflows

3. IPR (Instant Payment Reporting): Regulatory reporting to the Financial Sector Supervisory Commission (CSSF)

● Development of pipelines for data collection, transformation, aggregation, and XBRL generation

● Management of deployment, scheduling, and documentation

4. AML (Anti-Money Laundering) Project:

● Pipeline improvement and maintenance

● Data discrepancy analysis and implementation of fixes

● Migration from ODI to DBT Snowflake

● Optimization of processes through parallel execution

● Generation of XML files compliant with regulatory XSDs

5. Observability:

● Monitoring and anomaly detection

● KPI definition

● Creation of Power BI dashboards

Environment: Oracle, ODI, SQL, PLSQL, Python, Pandas, DBT, Snowflake, Shell Script, PowerBi, Jira, Gitlab, T24 (Temenos), TWS

Within the Remarketing department of ALD Automotive, I held the position of Data Project Manager within the Data Squad:

- Audit of the existing pipeline and proposal of improvement, simplification, and execution time reduction solutions.

- Documentation of the data loading pipeline.

- Responsible for the proper functioning of the pipeline.

- Production monitoring.

- Study, documentation, and validation of the architecture for various needs.

- Development responsibilities:

• Ingestion and historical storage of raw data in the Data Lake.

• Data transformation.

• Data Warehouse population.

• Calculation and population of Salesforce fields.

• Calculation of new KPIs and modification of the SSAS tabular model.

Environment: Python, Spark (Pyspark), Databricks, Microsoft Azure, Azure Storage Account, KeyVault, Azure Data Factory, PowerBi, SQL Server, SSAS, DAX, Azure DevOps (Azure Pipeline CI/CD, Azure Boards, Azure Repos), Jira, Confluence

Data Engineer (Big Data)

Danone, Ile de France

Within the R&I (Research & Innovation) team at Danone, responsible for several Big Data projects:

1. YWS: An application for scanning products:

• Project architecture definition.

• Data model definition.

• Implementation of translation via Google API.

• Development of the workflow (Ingestion of raw data from YWS, data translation and transformation, data cleaning, historical storage, population of DWH and various DTMs).

• Project monitoring and maintenance.

• Scheduling and log management.

• Use of APIs to enrich YWS with data from multiple countries and data homogenization.

• Master data management.

2. Data Quality:

• In collaboration with the business, definition of standards and control rules.

• Development of the workflow with Spark.

• Implementation of indicators.

• Scheduling.

3. CICD:

Development of a sample project for CICD with Jenkins:

• Use of BEHAVE for BDD tests.

• Unit tests.

• Use of SonarCloud for data quality.

• Production deployment.

4. Migration of scripts and data from the on-premise cluster to the new Danone platform based on Microsoft Azure.

5. Confluence Documentation.

6. Supervision of development carried out by interns.

Shell script, Python, Spark, Pyspark, Hadoop, Hdfs, Hive, Impala, Hue, Snowflake, Databricks, Microsoft Azure, Azure Data Factory, PowerBi, storage account, KeyVault, Jenkins, Github Action, SonarCloud, Git, Jira, Confluence, Intellij, Data Quality, Behave, Great Expectation