Digital Health Data Engineer

Axiom Software Solutions Limited; Eu; Hybride; EUR 60 000 - 90 000; Plein temps

Résumé du poste

A leading software solutions company is seeking a Digital Health Data Engineer to develop advanced data pipelines and analyse multimodal time-series data from biosensors. The ideal candidate will have 5+ years of experience in data engineering, strong Python skills, and expertise in cloud technologies like AWS and Azure. This remote position focuses on driving innovation in digital health applications, requiring excellent communication skills and a solid background in machine learning.

Qualifications

• 5+ years of industry experience for Bachelor’s or 3+ years for Master’s.
• Proficient in Python, able to mentor team members.
• Strong background in machine learning for large datasets.

Responsabilités

• Design and maintain data pipelines for large datasets.
• Utilize LLMs for innovative digital health applications.
• Support team members in solving Python-related queries.

Connaissances

Python

Data visualization

Machine learning

SQL

Bioinformatics

Communication skills

Formation

Bachelor's degree in CS/Data Science/Bioinformatics

Master's degree with relevant experience

Outils

AWS

Azure

PostgreSQL

Tableau

Docker

Description du poste

Job Title: Digital Health Data Engineer

Location: Remote (EU-based candidates only)

Duration: 6-12 months contract

We are looking for an outstanding digital health data engineer whose responsibilities will include:

Position Summary: We are seeking a Digital Health Data Engineer with expertise in analysing multimodal time-series data from biosensors (e.g., accelerometer, ECG, PPG, EEG) and developing advanced data pipelines for digital health applications. The ideal candidate will have experience with Python, cloud-native solutions (AWS, Azure, GCP), machine learning, and familiarity with generative AI (Gen AI) and large language models (LLMs), focusing on the development of digital biomarkers. This role will lead data exploration efforts, drive technical innovation, and collaborate across teams to advance healthcare solutions through development of digital biomarkers.

3+ Years exp is required.

Responsibilities

1. Design, build, and maintain data pipelines, ensuring seamless integration and high-performance processing of large-scale datasets.
2. Using large language models (LLMs) and foundation models, leveraging their capabilities for digital health applications and innovative solutions.
3. Provide Python expertise, supporting team members with queries and troubleshooting, while driving best practices in code quality and development.
4. Manage and optimize cloud infrastructure (AWS and Azure), including databases, Kubernetes clusters, AWS Bedrock, Athena, and S3 integration.
5. Drive technical innovation by implementing generative AI technologies such as RAG (Retrieval-Augmented Generation) and exploring applications in digital health data.
6. Communicate results through reports, presentations, and documentation.

Qualifications

Required:

1. Bachelor's degree with at least 5 years of industry experience or a Master’s degree with at least 3 years of industry experience in Computer Science, Data Science, Bioinformatics, or a related quantitative field.
2. Strong and proficient in Python, with the ability to mentor and assist the team in solving complex Python-related queries.
3. Experience in data visualization for complex datasets, especially of large-scale datasets and time series data, with a strong understanding of tools and techniques such as Tableau, Power BI, or similar platforms for presenting insights effectively.
4. Expertise in SQL, PySpark, and Dask for data engineering and analysis.
5. Proficiency in working with relational and cloud databases, including PostgreSQL and Redshift.
6. Strong background in machine learning, especially for large datasets.
7. Familiarity with healthcare systems, digital health, and cloud technologies (AWS, Azure, GCP, Snowflake).
8. Experience in digital health, physiological signal processing, and bioinformatics.
9. Excellent communication skills for collaborating and presenting technical concepts.

Nice to Have

1. Experience in multimodal time-series data (e.g., Accelerometer, ECG, PPG, EEG, etc.) from biosensors.
2. Knowledge of GPU computing, high-performance computing, and cloud-native applications.
3. Knowledge of containerization tools like Docker and their application in deploying data workflows.
4. Familiarity with cardiovascular, neuroscience, or epidemiology data
5. Experience in FDA submissions, validation, and working within GxP environments.