Staff Data Platform Engineer, Qventus

• You should be strongly motivated to have an impact in the company and dedicated to helping improve the quality of healthcare and patient outcomes
• Excellent cross-functional communication - the ability to break down complex technical components & drive technical decision-making across cross-functional teams
• Mastery in quality data modeling & data pipeline design, development, and optimization on both batch & streaming systems to create reliable, modular, secure data foundations
• Practical hands-on experience with various data platforms & technologies (Databricks, Snowflake, DBT, Spark, AWS ecosystem) and utilizing experience to drive technology changes to maximize performance while balancing system complexity
• Proficiency in microservices & event-driven architecture (AWS Lambda, Fargate, Kafka)
• Strong software development foundations - dedication to high code quality, stable architecture, and an eye toward maintainability
• Familiarity with MLOps, LLMOps, and the lifecycle of AI/ML model development; Hands-on experience working with Data Scientists to operationalize AI/ML services

Desirable

• As a Data Lead at Qventus, you will straddle software engineering, data platform pipeline & architecture, and data science to power advanced Gen AI-based solutions
• You will have a strong product mindset when it comes to data and drive key decision-making that balances speed, ease of use, and stability to ensure successful product development, both long and short-term
• You will design, implement, and lead the development of scalable and efficient batch & streaming pipelines
• You will collaborate with data experts across the organization to ensure our core Data Platform architecture vision & roadmap serves the needs of the Gen AI and associated products
• Develop and execute a cohesive data architecture within the AI operational assistant platform, ensuring alignment with the broader data platform and Chief AI Architect’s vision and fostering shared infrastructure and best practices across the organization
• Align with stakeholders across data, AI, product, and leadership teams on technical designs, upcoming priorities, and dependencies to ensure timely & stable delivery of key initiatives
• Translate product vision into highly functional data pipelines supporting high quality & highly trusted data products (incl. designing data structures, building and scheduling data transformation pipelines, improving transparency etc.)
• Proven ability to independently handle ambiguous requirements and lead data initiatives from start to finish while collaborating extensively with cross-functional, non-technical teams to inform and shape technical development