Forward Deployed Data Engineer

<div class="content-intro"><div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden; max-width: 100%; margin: 0 auto;"><iframe style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;" src="https://www.youtube.com/embed/Bp2Bw5VlpBI?si=aF6cux2K4H_farsI" width="560" height="315"></iframe></div> <p data-pm-slice="1 1 []"> </p> <p data-pm-slice="1 1 []">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.</p> <p>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. <span style="color: rgb(67, 32, 97);">#LI-JB1</span></p> <p> </p></div><p><strong>The Role</strong></p> <p>Forward Deployed Data Engineers at Qventus collaborate directly with clients to identify their most critical data challenges and design scalable, high-performance pipelines and architectures to solve them. Our customers depend on Qventus’ data infrastructure for mission-critical healthcare operations, and projects often start with broad, high-impact questions like, “How can we unify real-time surgical, staffing, and patient flow data into a single source of truth?” or “What’s the most efficient way to process and serve operational data for instant decision-making?”</p> <p>As a Data Engineer, you’ll combine technical expertise in large-scale data systems with a deep understanding of operational needs to create solutions that bridge the gap between raw data and actionable insights. You’ll work closely with data scientists, software engineers, and product teams to ensure our data pipelines are robust, efficient, and ready to support advanced analytics, AI models, and production-grade applications.</p> <p>You’ll operate in small, agile teams with significant autonomy, taking projects from initial scoping and design through to deployment and ongoing optimization. A typical day might involve architecting cloud-based ETL workflows, optimizing query performance on multi-terabyte datasets, integrating disparate hospital data systems, or collaborating with client IT teams to ensure seamless adoption.</p> <p><strong>Key Responsibilities</strong></p> <ul> <li>Design, build, and maintain scalable data pipelines and architectures to support analytics, machine learning, and operational applications.</li> <li>Collaborate with cross-functional teams to translate complex operational needs into reliable, well-modeled datasets.</li> <li>Integrate and normalize data from multiple structured and unstructured healthcare sources (EHRs, scheduling systems, operational databases, etc.).</li> <li>Optimize query performance and data processing for speed, scalability, and cost efficiency.</li> <li>Implement best practices for data quality, governance, and security in compliance with healthcare regulations (e.g., HIPAA).</li> <li>Support deployment, monitoring, and troubleshooting of production data systems.</li> </ul> <p><strong>What We’re Looking For</strong></p> <ul> <li>Proven experience as a data engineer or in a similar role, with a track record of building and maintaining large-scale data infrastructure.</li> <li>Strong proficiency in SQL and Python for data processing and pipeline development.</li> <li>Experience with cloud data platforms and services such as AWS (RDS, Redshift, Lambda, S3), GCP, or Azure.</li> <li>Knowledge of both relational and non-relational databases (PostgreSQL, MySQL, MongoDB, etc.). ... (truncated, view full listing at source)