Qventus

Senior Data Platform Engineer

Remote US
USD 150k - 185k
Machine Learning Azure AWS Spark
Description

About us:

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.

The role:

As a Senior Data Platform Engineer, you will lead the design, development, and management across investments to platform and data pipelines. You will identify, monitor, and lead initiatives to ensure our data platform (including both the core pipeline frameworks, warehousing, and ML Ops platform) remains scalable, reliable, and efficient in light of evolving requirements of our products and services. You will work closely with solution experts to identify missing platform functionality and areas for organizational optimization, and lead new build or optimization initiatives. You will be adept in partnering with cross-functional partners and data users to translate needs into technical solutions and leading the technical scoping, implementation, and general execution of improvements to our solutions and platform. You will be data curious and excited to have an impact on the team and in the company and to improve the quality of healthcare operations.

Key Responsibilities

  • Lead scoping and execution of critical improvements to our data platform to maintain overall system health and improve data observability in lieu of changing product needs and to optimize innovation velocity

  • Provide expertise on the overall data engineering best practices, standards, architectural approaches and complex technical resolutions

  • When needed support solution development; translate product / analytical 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.).

Key Qualifications

  • Strong cross-functional communication - ability to break down complex technical components for technical and non-technical partners alike

  • Experience working with Data Science teams to support ML Ops

  • Excellence in quality data pipeline design, development, and optimization to create reliable, modular, secure data foundations for the organization's data delivery system from applications to analytics & ML

  • Experience building, designing, and/or developing on a diverse set of modern data architecture designs and their relative capabilities and use cases (ex. Data Lake, Lakehouse, Lambda)

Nice to Have Skills

  • 3+ years of experience designing, building, and operating cloud-based, highly available, observable, and scalable data platforms utilizing large, diverse data sets in production to meet ambiguous business needs

  • Interest in mentoring and supporting new developers

  • Robust aptitude for interpreting complex datasets, including the ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills.

  • Relevant industry certifications in a variety of Data Architecture services (SnowPro Advanced Architect, Azure Solutions Architect Expert, AWS Solutions Architect / Database, Databricks Data Engineer / Spark / Platform etc.)

  • Experience designing and supporting multi-cloud architectures (particularly for ML / AI systems)

  • Experience with data visualization tools and analytics technologies (Looker, Tableau, etc.)

  • Degree in Computer Science, Engineering, or related field

  • Experience working with healthcare data and HIPAA data protection

The salary range for this role is $150,000 to $185,000. 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 bonus, 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 to 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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