Data Preparation

il y a 5 jours


Luxembourg NTT DATA Temps plein

**Make an impact with NTT DATA**
Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion - it’s a place where you can grow, belong and thrive.

**Topic**:
Design and implement a Data Preparation & Privacy Toolkit for use at the SPE boundary. The toolkit will:

- Ingest and export FHIR resources using an open-source server (e.g., HAPI FHIR).
- Generate synthetic datasets for non-sensitive pipeline testing (using SDV).
- Document repeatable, Infrastructure-as-Code style steps suitable for DS4L’s Product Phase.

The goal is to provide DS4L with a standardized, safe, and reproducible method to prepare health data before it enters any connector or dataspace workflow.

**Your role will consist in**:

- Setting up and testing a local HAPI FHIR server with sample resources.
- Implementing PII detection/redaction in free-text fields (Presidio).
- Exploring synthetic data generation for testing and demo scenarios (SDV).
- Creating a policy pack with anonymization presets and PII detection rules.

During the internship, you will receive the support of a senior engineer as well as the team leader to guide you while defining the approach and milestones. You will also have the opportunity to participate in all the team meetings, which will enable you to be immersed in the professional world and to be faced with day-to-day challenges encountered in the work.

**Prerequisites**:

- Proficiency in Python (pandas, scripting).
- Basic Docker/Linux/Git skills.
- Understanding of data handling and security best practices.
- Ability to read and work with FHIR resources.
- Strong interest in privacy engineering and reproducibility.

**Good to have**:

- Knowledge of data anonymization frameworks (e.g., ARX).
- Experience with synthetic data generation (SDV or similar).
- Familiarity with Kubernetes or Infrastructure-as-Code approaches.
- Basic statistics/ML to interpret utility vs. privacy trade-offs.
- Awareness of OMOP CDM or health data standards beyond FHIR.

**Soft skills**:

- Autonomy
- Organization / Planning
- Collaboration

**Workplace type**:
On-site Working

**About NTT DATA**

**Equal Opportunity Employer**

**Third parties fraudulently posing as NTT DATA recruiters


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