Overview

Excellent opportunity to work REMOTELY with a U.S.-based company. Candidates living in Mexico, or all LATAM are welcome to apply.

About The Company

Bydrec, Inc. is a California-based company that connects top Tech talent from Latin America with U.S. companies looking to expand their development teams. Learn more at bydrec.com.

Position Summary

We are seeking a Digital Health Data Engineer with expertise in extracting features and analyzing multimodal time-series data from biosensors such as accelerometer, ECG, PPG, and EEG. This role will also focus on developing advanced data pipelines for digital health applications , including audio and video data processing .

The adecuado candidate has strong experience with Python, cloud-native architectures, AWS Batch, containerization, and time-series databases . This person will lead data exploration initiatives , drive technical innovation , and collaborate across teams to advance healthcare solutions through the development of digital biomarkers .

Responsibilities

- Design, build, and maintain data pipelines to ensure seamless integration and high-performance processing of large-scale time-series datasets.
- Develop rapid QC metrics used in dashboards to present complex datasets to stakeholders.
- Provide Python expertise, supporting team members with queries and troubleshooting while promoting best practices in code quality and development.
- Communicate insights and results through reports, presentations, and technical documentation.

Qualifications

Required :

- Bachelor’s degree with 5+ years of industry experience, or a Master’s degree with 3+ years of experience, in Computer Science, Data Science, Bioinformatics,



or a related quantitative field.
- Advanced English proficiency (written and spoken).
- Strong proficiency in Python, with the ability to mentor and support the team in solving complex Python-related challenges. Proficiency in R is also required.
- Experience in data visualization for complex and large-scale datasets, particularly time-series data, using tools such as Power BI.
- Expertise in SQL, PySpark, and Ray clusters for data engineering and large-scale analysis.
- Experience with containerization tools such as Docker and deploying data workflows in modern environments.
- Hands-on experience with machine learning, particularly with large datasets.
- Familiarity with cloud technologies, including AWS and Snowflake.
- Experience working with multimodal time-series biosensor data such as accelerometer, ECG, PPG, or EEG.
- Strong communication skills, with the ability to collaborate across teams and present complex technical concepts clearly.

Nice To Have

- Familiarity with large language models (LLMs) and applying generative AI approaches such as Retrieval-Augmented Generation (RAG) in digital health environments.
- Knowledge of GPU computing, high-performance computing, and cloud-native architectures.
- Experience with relational and cloud databases, including PostgreSQL and Redshift.
- Hands-on experience managing and optimizing cloud infrastructure using AWS and Snowflake, including tools such as Kubernetes, AWS Bedrock, AWS Batch, Athena, AWS Glue, KIRO, and S3 integrations.
- Familiarity with cardiovascular, neuroscience, or epidemiology datasets.
- Experience with FDA submissions, validation processes, and working within GxP environments.

📌 Digital Health Data Engineer (Colombia)
🏢 Bydrec
📍 Colombia