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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** HORIZON SURGICAL, INC. - **Location:** Los Angeles, CA, United States - **Experience:** Experienced - **Salary:** $120,000.0 - $134,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Cloud Computing, Cloud Storage, Code Review, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Data Transformation, Data Warehousing, Dicom, Python (Programming Language), Machine Learning, DataOps, Robotic Automation Software, Software Engineering, SQL Databases, Management of Software Versions, Data Ingestion, Snowflake, Model Validation, Git, Data Lakes, Kubernetes, Information Technology, Data Inconsistencies, Software Version Control, Data Pipelines - **Published:** June 20, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=3f9c92b446fa7e41 ## About the Role Do you have experience in Version control systems?, Do you have a Bachelor's degree?, * 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. ## Description The Data Engineer is responsible for designing, building, and maintaining the data pipelines that power AI model training, validation, and regulatory workflows for autonomous surgical robotics systems. Working alongside the Data Operations Analyst, this role focuses on the engineering side of the data lifecycle: architecting reliable, scalable pipelines in Dagster, modeling data in SQL, and writing production-quality Python. The ideal candidate brings strong fundamentals in SQL and Python; and is eager to deepen their data engineering expertise in a fast-paced, regulated environment., * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [ZEISS & Microsoft - Building the Next Generation Medical Ecosystem in the Cloud](https://www.wearedevelopers.com/videos/424-zeiss-microsoft-building-the-next-generation-medical-ecosystem-in-the-cloud) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)