Staff Data Engineer - AQMed

AQMed is revolutionizing diagnostics, starting with CardiAQ™, a noninvasive device set to tackle the world's leading cause of death. Cardiovascular disease diagnostics are ripe for disruption, and CardiAQ™ is our answer—a device utilizing sophisticated magnetocardiography (MCG) enhanced by AI to offer faster, more accurate results than ever before.

This groundbreaking innovation hinges on mastering the torrent of complex data it generates. We seek a visionary Staff Data Engineer for Operations to architect and command this critical asset. Your primary directive will be forging the robust, scalable infrastructure needed to transform raw data into revolutionary insights. You will take full ownership of our AWS data backbone, engineering a streamlined, reliable system from a challenging, growing dataset. By empowering our scientific pioneers with pristine data, you will directly accelerate discovery and impact the future of healthcare in our dynamic startup environment. This is your opportunity to build, to own, and to leave your mark.

• Design and manage scalable data pipelines on AWS to support AI-driven medical research.
• Oversee core data systems, ensuring high uptime, data quality, and efficient batch workflows.
• Create and refine data ingestion, transformation, and storage processes for research use.
• Automate data processing pipelines to improve reliability, speed, and reproducibility.
• Build and maintain automated ML training and reporting workflows to support model development and monitoring.
• Use AWS services (like S3 and related tools) to build cost-effective, reliable data solutions.
• Develop and enforce consistent data practices, architecture, and documentation.
• Work closely with scientists, ML engineers, and medical experts to meet data needs.
• Build data systems that meet healthcare regulations and prioritize privacy.

• Bachelor's or Master's Degree in Computer Science, Computer Engineering, Mathematics, Physics, Statistics, or other relevant technical discipline. 
• 8+ years of experience as a Data Engineer, focusing on data operations.
• Extensive experience working with large datasets in a cloud environment, specifically AWS.
• Strong proficiency in AWS data tools and services (e.g., S3).
• Experience with data pipeline development and batch processing.
• Experience with programming languages related to data engineering tools and frameworks such as Spark, Scala, Hadoop, Python, or similar.
• Proficiency with SQL and databases 
• Comfortable working in a collaborative, fast-paced team with a strong mission.
• Proactive, self-driven, and excited to learn new technologies and approaches.
• Demonstrates strong ownership by proactively taking initiative, accountability, and attention to detail.

• Exposure to multichannel sensor data or time series data (e.g., ECG/EKG, medical device data)
• Experience with MLOps and exposure to machine learning workflows

The US base salary range for this full-time position is expected to be $192K - $269K per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.