Data Engineer - Pharma B2B Contract

Length of Contract : 6 month contract, temporary support to help with projects. Possibility of extension.

Location: Can be remote but Barcelona preferred

Role Overview

We are seeking a highly skilled and motivated data engineer to support our R&D IT partners by extracting and matching bio-sample identifiers with other internal datasets. These efforts will enhance research activities and contribute to the utility of our newly developed GenAI capability.

The successful candidate will have a strong technical background in data modelling, data forensics, databases, Python, APIs, testing, Git and CI / CD pipelines.

This is a unique opportunity to play a critical role in modernising our clients' data science infrastructure, enabling teams to collaborate, experiment, and deploy AI / ML models at scale.

Key Responsibilities :

1. Apply excellent abstraction and analytical capabilities to perform data transformations and enable the connection of datasets, thinking outside the box as needed
2. Extract data from existing internal sources
3. Extract identifiers from existing platforms
4. Build data model to link regulated and sensitive data
5. Collaborate with cross-functional teams, including data scientists, engineers, and IT, to ensure seamless integration of systems
6. Develop and maintain the code following best code and engineering practices
7. Automate deployment processes to ensure rapid and reliable delivery of projects
8. Troubleshoot and resolve issues related to data access, API integrations, and migration
9. Document processes, workflows, and technical guidelines to support knowledge transfer.

Required Qualifications :

1. Proven experience in data modelling and databases
2. Strong programming skills in Python, with a focus on data science or software engineering and code quality standards.
3. Strong SQL, Spark, and PySpark with a focus on interrogating and deploying data
4. Hands-on experience with CI / CD tools and pipelines (e.g., Jenkins and GitHub Actions).
5. Expertise in automated deployment and reproducible workflows.
6. Familiarity with cloud platforms (e.g., AWS) and their integration with data science tools.

Preferred Qualifications :

1. Strong understanding of data modelling and databases
2. Excellent problem-solving skills with a proactive and collaborative mindset.
3. Strong communication skills to work with diverse teams and explain technical concepts clearly.