Quality and Validation Engineer M/F

As part of a digital transformation and operational performance improvement project, you will join a team dedicated to operational data quality.

Your role will be to analyze data, identify anomalies, and contribute to the implementation of improvement actions. You will thus participate in ensuring the reliability of data used in the fields of production, quality, and supply chain.

Your main missions

Analysis and quality control of data

Understand operational data, business processes, information management tools, and data flows.

Audit data flows and structures to identify anomalies, inconsistencies, missing values, or incomplete data.

Analyze data content, trends, and patterns to detect quality issues.

Identify the root causes of errors and propose corrective actions.

Correct, update, or delete incorrect or incomplete data.

Define rules and controls to ensure data compliance with business and regulatory requirements.

Steering data quality improvement

Define and implement a data quality improvement plan with the relevant stakeholders.

Identify business interlocutors to gather functional knowledge and business logic related to the data.

Define and deploy quality controls on Master Data.

Monitor the progress of improvement actions and ensure reporting.

Identify, document, and escalate risks, difficulties, and bottlenecks.

Support business and technical teams in resolving data quality issues.

Profile sought

You have a degree in higher education in data analysis, computer science, quality, supply chain, data management, or a similar field.

You have a minimum of 3 to 5 years of professional experience, ideally acquired in one of the following environments:

Procurement / Purchasing;

Quality;

Supply Chain;

Operational data analysis;

Data management or governance.

Experience in an industrial environment or knowledge of processes and tools used in the aeronautics sector would be appreciated. Previous professional experience within the group is also an asset.

Technical skills

Mastery of data analysis and quality control.

Good proficiency in SQL to query and analyze databases.

Knowledge of Python or R.

Experience with tools such as SAP, SAP HANA, or Skywise.

Understanding of data flows and operational business processes.

Knowledge of data governance.

Ability to identify root causes and solve complex problems.

Personal qualities

Analytical mind and keen attention to detail.

Curiosity and a taste for investigation.

Autonomy and ability to take initiative.

Rigor in analysis and monitoring of actions.

Interpersonal skills and ability to communicate with both technical and non-technical interlocutors.

Ability to work in a team within an international and multicultural environment.

Ability to manage stakeholder expectations and coordinate different interlocutors.

Sense of integrity and vigilance regarding compliance risks.

Languages

English: fluent professional level, indispensable for operating in an international environment.