Data Engineer Thales

As Data Engineer, you will participate in the different phases of Thales Digital Transformation Projects by collecting, modeling, and rendering our data in order to help end user to perform an accurate analysis of their business through reports and Dashboards.

Roles and Responsibilities

• Assembling large, complex sets of data that meet non-functional and functional business requirements
• Developing reusable ETL Jobs use cases
• Conception of connectors/jobs
• Development of Talend Jobs, deployment and commissioning of the interfaces
• Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
• Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using ETL and SQL technologies
• Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
• Significate experience on data engineering Cloud environment (azure), especially on data services (incl. ADLS Gen 2, Synapse, ADF, Azure SQL DB, Analysis Services, Power Bi Services
• Highly skilled in Microsoft SQL Server Stack (Data Base Engine, Integration Services, Analysis Services, Power BI Reporting Services
• Advanced SQL, DAX, MDX and Query performance tuning Skills
• Very good Knowledge on Design Pattern of Data Product
• Demonstrate ability to manage multiple interfaces & deal with IT resources in international context
• Familiar with fully automated CI/CD Pipelines (Azure DevOps) for code deployment, integration and test automation, code quality and orchestration for automated build and release.
• Ability to manage Row Level Security on each Layer of the data Chain
• Familiar with ETL Feeding mechanisms (Delta/Full Loading ,Historical data)
• Experience Building and Interacting with Data Lake Solutions
• Good knowledge on agile methodology
• Working with stakeholders including data, design, product and executive teams and assisting them with data-related technical issues
• Build Data Warehouses, Data Marts and Data Cubes
• Maintain the ETL in operational condition
• Working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues
• Experience using dbt for data transformation and modeling.
• Familiarity with distributed query engines such as Trino (or equivalent).
• Knowledge of object storage systems such as MinIO (or equivalent).
• Strong understanding of modern data architectures, including the medallion architecture
• Nice to have: Experience with scalable data pipelines on GCP (BigQuery, GCP, Dataproc)
• Support the qualification of the projects, extraction, transformation and load of the data (Data Scoping / Discovery)
• Technical Framing : Feasibility study, expression of needs, estimation of the load and timeframe
• Writing Technical Specifications
• Ensure documentation of achievements
• Enrich solution components catalogue
• User Support
• Customer oriented
• Quality minded and proactive approach