Data Engineer
Indexed description
We are seeking highly motivated, and intellectually inquisitive individuals looking to make a positive impact on healthcare via the development of robotic technology. The core values of Horizon Surgical Systems Inc. are:
- Commitment to Excellence: We aim to deliver superior patient outcomes and surgeon experiences
- Passion for Creativity and Innovation: We are driven by new ideas and aim to push the boundaries of what's possible
- Teamwork and Camaraderie: We achieve our best when we collaborate and work together
- Welcoming of Critical Opinion: We are enriched by constructive criticism and support the best ideas
- Personal Accountability: We honor our commitments and take responsibility for our actions
- An opportunity to build autonomous surgical robotic systems driven by image guidance and AI technology for the future of affordable, high-quality healthcare.
- The opportunity to work alongside clinicians, engineers, and global leaders in cutting-edge AI, imaging, and robotics technology.
- Competitive compensation and an excellent company-paid benefits package.
Essential Duties And Responsibilities
- Design, build, and maintain data pipelines in Dagster to support AI model training, validation, and regulatory submission workflows.
- Write and optimize SQL for data transformation, modeling, and quality validation across the data platform.
- Develop Python-based tooling and automation to support data ingestion, transformation, and delivery.
- Collaborate with the Data Operations team to ensure pipeline outputs meet data quality, traceability, and compliance requirements.
- Build and maintain infrastructure for data ingestion from surgical robotic systems, annotation platforms, and internal sources into cloud storage (AWS S3).
- Implement data validation, testing, and monitoring within pipelines to catch anomalies and ensure data integrity.
- Support dataset versioning and lineage tracking to satisfy IEC 62304 and FDA Design History File requirements.
- Contribute to the design of data models, schemas, and catalogs in coordination with the Data Operations team.
- Troubleshoot and resolve pipeline failures, performance bottlenecks, and data inconsistencies.
- Participate in code reviews and contribute to engineering best practices for the data platform.
- Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field, or equivalent practical experience.
- 2+ years of experience in data engineering, software engineering, or a related technical role.
- Strong proficiency in SQL for data transformation and analysis.
- Strong proficiency in Python for building data pipelines and automation.
- Experience with cloud infrastructure (AWS preferred) and containerized workflows.
- Familiarity with version control (Git) and collaborative development workflows.
- Eagerness to learn and grow in data engineering, including orchestration frameworks, data modeling, and infrastructure-as-code.
- Effective communication skills for working closely with analysts, ML engineers, and cross-functional teams.
- Experience with Dagster or similar orchestration frameworks (Airflow, Prefect).
- Experience with data warehouse or lakehouse patterns (e.g., Snowflake, Delta Lake, dbt).
- Exposure to regulated environments (FDA, ISO 13485, IEC 62304) or medical device industry.
- Familiarity with machine learning data lifecycle concepts (dataset versioning, data drift monitoring, model validation datasets).
- Knowledge of DICOM, medical imaging data standards, or ophthalmic imaging modalities (OCT, microscopy) is a plus.
The base salary range for this role is $120,000 - $134,000, in addition to a performance-based annual bonus, equity (stock options), a comprehensive benefits package, and a generous PTO policy.
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search