Digital Health Data Engineer (Medtech)

TL;DR

Digital Health Data Engineer (Python/AWS): Developing and optimizing data pipelines for multimodal time-series biosensor data with an accent on feature extraction and digital biomarkers. Focus on building large-scale data workflows, processing audio/video health data, and implementing advanced QC metrics for stakeholders.

Location: Remote (LATAM) - Candidates must be based in Mexico or Latin America

Company

hirify.global connects top technical talent from Latin America with U.S.-based companies to expand their development teams.

What you will do

• Design, build, and maintain high-performance data pipelines for large-scale time-series datasets.
• Develop rapid QC metrics and dashboards to visualize complex datasets for stakeholders.
• Provide Python expertise and mentorship to team members to ensure high code quality.
• Communicate technical insights and results through comprehensive reports and documentation.

Requirements

• Bachelor's degree with 5+ years of industry experience, or Master's degree with 3+ years in Computer Science, Data Science, Bioinformatics, or related field.
• Advanced English proficiency (written and spoken).
• Strong proficiency in Python and R.
• Expertise in SQL, PySpark, Ray clusters, and Docker for large-scale analysis.
• Hands-on experience with multimodal time-series biosensor data (e.g., ECG, PPG, EEG, accelerometer).
• Must be based in Mexico or Latin America (LATAM).

Nice to have

• Familiarity with LLMs and generative AI approaches such as RAG in digital health environments.
• Knowledge of GPU computing, high-performance computing, and cloud-native architectures.
• Experience managing AWS infrastructure (Bedrock, Batch, Athena, Glue) and Snowflake.
• Knowledge of cardiovascular, neuroscience, or epidemiology datasets.
• Experience with FDA submissions, validation processes, and GxP environments.