At Orakl Oncology, we transform vast volumes of clinical and genomic data from internal and external sources into actionable insights that drive groundbreaking oncology research. Our ability to deliver cutting-edge solutions to our customers hinges on a robust, scalable, and intelligent data infrastructure.

We are seeking a Senior Software Engineer to take the lead in designing and optimizing our data workflows. In this key role, you will architect and maintain a seamless data pipeline, integrating complex and diverse datasets into our cloud ecosystem. Your work will empower our researchers and collaborators with high-quality, easily accessible clinical and genomic data—fueling innovations in precision oncology.

What You’ll Do

• Design Orakl Data Infrastructure: Partner with leadership to design and implement a scalable, high-performance coding infrastructure that supports our growing data needs.

• Automate & Streamline Data Integration: Build smart data pipelines to seamlessly ingest, clean, and integrate clinical and lab-generated data into our cloud environment.

• Shape & Optimize Our Data Lake: Develop and maintain data access tools that empower Data Scientists and Computational Biologists to effortlessly extract insights from Orakl’s Data Lake.

• Bridge Data Engineering & Genomics: Work hand-in-hand with Computational Biologists to deploy scalable, production-ready genomics pipelines, enhancing our ability to analyze complex biological data.

• Ensure Data Security & Compliance: Implement best-in-class security measures to safeguard sensitive data, while ensuring compliance with French and European healthcare privacy regulations (HDS).

Minimum Qualifications

• Engineering degree in Computer Science, Data Science or any related field.

• 5+ years of experience in a data-related role (Data Scientist, Research Scientist, Software Engineer).

• Expertise in cloud infrastructure and services (AWS preferred) and ETL/ELT processes (e.g., Talend, Airflow).

• Exceptional proficiency in Python programming.

• Track Record in building and shipping high quality solutions fast.

• Someone highly opinionated, experienced, and detail-oriented, with a proven track record in building scalable, secure, and efficient data solutions.

• A collaborative mindset with a strong desire to work closely in a multidisciplinary environment in close collaboration with data scientists, biologists, and clinicians.

Preferred Qualifications

• Experience in data engineering roles (ML Engineer, Data Engineer).

• Familiarity with AI/ML pipelines and MLOps (mlflow) & CI/CD processes (GitHub actions, Azure DevOps, Jenkins).

• Familiarity with CI/CD processes (e.g., GitHub Actions, Azure DevOps, Jenkins).

• Knowledge of containerization technologies (e.g., Docker).

First Interview (30-minute call) – An initial discussion to better understand your background, experiences, and motivations.

Second Interview (Technical Capabilities) – A deep dive into your technical skills and expertise relevant to the role.

Third Interview (Use-case) – A case study or problem-solving exercise to assess your strategic thinking and analytical abilities.

Fourth Interview (Technical Presentation) – A presentation you would be giving to our team about a project you enjoyed working on and you feel relevant for the role.

Fifth Interview (Cultural Fit) – A conversation with our team to ensure alignment with our company culture, values, and ways of working.