DataOps Analyst, Horizon Surgical Systems

• Bachelor's degree in Computer Science, Data Science, or a related field — or equivalent hands-on experience
• 2+ years of experience in a data operations, data engineering, or data analysis role
• Proficiency in Python for data manipulation, scripting, and automation
• Solid understanding of the AWS ecosystem (S3, Lambda, Glue, or similar services)
• Comfortable working in Linux environments and writing Bash scripts
• Git-fluent: version control is part of your daily workflow, not an afterthought
• You take data quality seriously and document your work clearly
• Good communicator — you can work with technical and non-technical stakeholders without losing them

Desirable

• We're looking for a sharp, curious DataOps Analyst to join the small but mighty data team at Horizon Surgical Systems
• You'll be on-site in Santa Monica, working closely with our principal DataOps engineer — someone with 10+ years of experience in data pipelines who'll be invested in your growth
• This is a hands-on role where you'll move and manage surgical data between Polaris, our cataract surgery platform, and our cloud environment where custom AI model training happens. If you're early in your career and want to do real, meaningful work in medical AI, this is a great place to grow
• Move and manage data between Polaris (our cataract surgery platform) and our AWS cloud training environment, keeping pipelines healthy and well-documented
• Build and maintain ETL/ELT workflows using Python and Bash, and help us make them more reliable over time
• Monitor pipeline health, catch anomalies early, and troubleshoot failures before they become problems
• Maintain data catalogs, versioning, and audit trails so our datasets stay traceable and well-organized
• Collaborate with our AI/ML engineers to curate, version, and validate training and test datasets
• Write scripts and automation tools that reduce manual data handling — Linux/Bash fluency matters here
• Support data requests from cross-functional teams including Regulatory, Clinical, and Systems Engineering
• Generate dashboards and reports on pipeline health, data quality, and throughput metrics
• You'll be mentored directly by our principal DataOps engineer, who has 10 years of experience building and running production data pipelines
• This isn't a role where you'll be thrown in the deep end alone — you'll have real guidance and support as you ramp up. That said, we're a startup, so the work is real from day one and the pace is honest