Key responsibilities :

- Develop and maintain scalable data pipelines using Python/Java/Scala/PySpark and Big Data tech (Hadoop, Spark, Scala).

- Build, train, and optimize ML models using frameworks like PyTorch, TensorFlow, Keras, and XGBoost.

- Design and manage real-time data workflows leveraging Kafka, SQL, and MongoDB.

- Create dashboards and insights using Tableau or Power BI to support decision-making.

- Utilize Cloud platforms (Azure/Databricks) to deploy and operationalize data and ML solutions.

- Ensure the reliability, scalability, and performance of our data assets.

- Design and maintain quality indicators as well as the corresponding monitoring and alerting means.

- Troubleshoot and document issues respecting Amadeus standards.

- Continuous improvement mindset applied to data related issues, systems, and processes.

- Technical and expertise awareness to keep up with industry standards, security recommendations and best practices within Offer organization.

Cloud & Analytics :

- Deploy and operationalize data and ML solutions on Microsoft Azure.

- Work with :

1. Azure Databricks

2. Azure Machine Learning

3. Databricks SQL

- Create business dashboards and reports using :

1. Tableau

2. Power BI

- Familiarity with Snowflake Data Cloud will be an added advantage.

Testing & Support :

- Conduct unit, integration, and performance testing.

- Participate in product validation and quality assurance activities.

- Investigate model behavior and provide production support.

- Troubleshoot issues and document resolutions following organizational standards.

About the ideal candidate :

- Analyze specifications, help to define user requirements for the development of software solutions.

- Design and development.

- Design technical solutions and perform feasibility studies.

- Propose viable technical solutions.

- Develop software according to Amadeus standards.

- Data Engineering Activities :

1. Acquire datasets that align with business needs.

2. Develop algorithms to transform data into useful, actionable information.

3. Design, develop, construct, test, and maintain optimal data pipeline architectures.

4. Create new data validation methods and data analysis tools.

5. Ensure compliance with data governance and security policies.

6. Identify ways to improve data reliability, efficiency, and quality.

- Data Science activities :

1. ML Model training.

2. ML Model calibration for different customers.

3. KPI definition and measurements.

4. Data mining, data analysis.

5. Research.

6. Design new algorithms / models. Enhance the existing ones.

7. Industrialize and implement new prototypes.

- Test and support :

1. Conduct unit, package and performance tests and ensure a level of quality in line with the Amadeus guidelines.

2. Participate in the validation phase of the product cycle, fine-tuning when necessary to finalize the product.

3. Support the customer, perform investigation about the model result and behavior.

Cloud :

- Familiarity with Azure cloud technologies.

- Familiarity with Azure Databricks, Azure ML and Databricks SQL.

- Familiarity with Snowflake Data Cloud will be a plus.

Qualifications :

- Education : University degree in computer science or related field or relevant experience.

- Proven track record of experience working in Applied Machine Learning Concepts & Data Science area.

- Experience with data modeling and data visualization concepts and tools.

- Knowledge of Software Design under Agile frameworks (Scrum, Kanban, SAFe, ).

- Proven experience on design and maintaining applications using Scala, (Py)Spark, Kafka and NoSql databases.

- Hands-on experience on Microsoft Azure, Databricks.