Clinical Data Engineer: Pipelines, AI & Wearables

RECRUIT LYNC PTE. LTD.; Singapore; Sur place; SGD 70 000 - 120 000; Plein temps

Avantages offerts par ce poste

Completion bonus

Résumé du poste

Recruit Lync Pte Ltd in Singapore is seeking a Data Engineer to design, build and maintain data pipelines for digital health and clinical study data, ensure data quality, lineage and reproducibility, and support analytics-ready datasets across projects.

You will work with Python, SQL and cloud platforms (AWS/Azure/GCP), analyze wearable sensor and time-series data, apply ML/AI techniques, build internal APIs, and collaborate with data scientists and clinical teams to advance study objectives.

Qualifications

• Degree in CS/Data Engineering/Analytics/AI or related field.
• At least 3 years in data engineering, data analysis and algorithm development.
• Strong Python and SQL; cloud experience with AWS/Azure/GCP.

Responsabilités

• Design, build and maintain data pipelines for digital health and clinical study data.
• Manage data ingestion, transformation, storage, quality checks and delivery of analysis-ready datasets.
• Develop and maintain pipeline code using Python and SQL.
• Support analysis of wearable sensor and time-series data.
• Apply machine learning, deep learning and AI/LLM technologies to support digital health initiatives.
• Monitor data quality, troubleshoot pipeline issues and ensure data is traceable and reproducible.
• Build and maintain internal APIs and data platforms supporting AI and analytics applications.
• Collaborate with data scientists, clinical teams and stakeholders to support study objectives.
• Drive improvements in data processing efficiency, integrity and quality.

Connaissances

Python

SQL

Data pipelines

Time-series data

Formation

Bachelor's degree in Computer Science, Data Engineering, Analytics, AI or related discipline

Outils

AWS

Azure

GCP

APIs

Description du poste

Recruit Lync Pte Ltd in Singapore is seeking a Data Engineer to design, build and maintain data pipelines for digital health and clinical study data, ensure data quality, lineage and reproducibility, and support analytics-ready datasets across projects.

You will work with Python, SQL and cloud platforms (AWS/Azure/GCP), analyze wearable sensor and time-series data, apply ML/AI techniques, build internal APIs, and collaborate with data scientists and clinical teams to advance study objectives.