Senior Software Engineer (Data)

• Our generative AI-powered products are revolutionizing the practice of medicine, and we’re looking for a highly motivated Data Engineer to join our growing US-based Data Engineering team
• In this crucial role, you will build and optimize large scale data infrastructure to drive business decisions and machine learning research
• Build and maintain scalable data services, pipelines and storage solutions for the feedback of unstructured application data for ML training and evaluation purposes
• Build and manage OLAP databases, ELTs and general data tooling for analytics , business decisions and products features
• Work closely with a team of frontend and backend engineers, product managers, and analysts
• Optimize data infrastructure to enhance the throughput, latency and reliability of the data system
• Investigate and correct issues identified through data operations monitors, tools, and reports
• Designs data integrations and data quality framework

Benefits

• Flexible working hours — we care more about what you accomplish than what specific hours you’re working
• Unlimited PTO, plus 12 national holidays
• Remote work environment
• Equity for all new employees
• 16 weeks paid parental leave, for all employees
• Generous equipment budget for your home office setup ($1600)
• Opportunity to work and grow with talented individuals, and have ownership and impact at a high growth startup- 8+ years of experience in Data Engineering or Backend Engineering with a focus on data systems
• Proficiency with at least one modern cloud provider (GCP, AWS, Azure) and accompanying data services
• Experience in building data products that are well-modeled, documented and easy to understand and maintain
• Experience with distributed systems and different distributed processing frameworks
• Proficient in at least one general purpose programming language (e.g., Python, Java, Scala) and SQL (any variant)
• Experience with Terraform, Kubernetes, and containerization technologies
• Deep knowledge of modern data infrastructure best practices
• Ability to prioritize amidst changing priorities in a fast moving environment
• Experience in building systems that manage the ingest, transformation, and management of both structured and unstructured data types
• Familiarity with the deploying ML models at scale a bonus