Qventus

Staff Data Platform Engineer - GenAI

Remote US
USD 170k - 220k
Machine Learning Streaming Spark AWS Microservices Kafka
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Description

On this journey for over 12 years, Qventus is leading the transformation of healthcare. We enable hospitals to focus on what matters most: patient care. Our innovative solutions harness the power of machine learning, generative AI, and behavioral science to deliver exceptional outcomes and empower care teams to anticipate and resolve issues before they arise.

Our success in rapid scale across the globe is backed by some of the world's leading investors. At Qventus, you will have the opportunity to work with an exceptional, mission-driven team across the globe, and the ability to directly impact the lives of patients. We’re inspired to work with healthcare leaders on our founding vision and unlock world-class medicine through world-class operations.

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. You should be strongly motivated to have an impact in the company and dedicated to helping improve the quality of healthcare and patient outcomes.  What we do can meaningfully change and, in some cases, save lives.

Key Responsibilities:

  • 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.

What We’re Looking For: 

  • 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.

It’s a Plus if You Have… 

  • Proven experience in leading and mentoring technical teams, with a focus on both technical & soft skill development and project management.

  • Understanding of agentic workflows and finite state machines

  • Experience with healthcare data and industry

  • Strong understanding of Object-Oriented Programming and design patterns.

  • Master’s degree in Computer Science, Engineering, or related field, or equivalent training/experience

The salary range for this role is $170,000 to $220,000. Qventus salary bands represent market data across different geographies. We consider several factors when determining compensation, including location, skills and qualifications, and prior relevant experience. Salary is just one component of Qventus’ total package. Some of our key benefits and perks* include but are not limited to Open Paid Time Off, paid parental leave, professional development, wellness and technology stipends, generous employee referral bonuses, and employee stock option awards.

We believe that diversity, equity, inclusion, and belonging are fundamental to improving healthcare and society, and that’s why we’re building a company that leads the way. We hold ourselves accountable for using fair hiring processes that mitigate the negative impacts of unconscious bias. We also work to ensure that people from underrepresented groups play meaningful roles on both sides of the interview table. We are an equal opportunity employer and give all qualified applicants consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations, and ordinances.

Candidate information will be treated in accordance with our candidate privacy notice, which can be found here: https://qventus.com/ccpa-privacy-notice/

Employment is contingent upon the satisfactory completion of our pre-employment background investigation and drug test.

*Benefits and perks are subject to plan documents and may change at the company's discretion.

Qventus
Qventus
Analytics Artificial Intelligence (AI) Health Care Hospital Machine Learning

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