Senior Data Engineer

Qventus, Inc is leading the transformation of healthcare through innovative solutions that harness machine learning and AI. They are seeking a Senior Data Engineer to design, develop, and manage data assets and pipelines to support their products and improve healthcare operations.

Responsibilities:

• Spearhead the discovery, evaluation, and integration of new datasets, collaborating (incl. pipeline development and data modeling/documentation) working closely with key data stakeholders to understand their impact and relevance to our core products and the healthcare domain
• Facilitate the technical management of data assets - clearly tracking and maintaining context on the data within the dataset lifecycle and sustaining tight partnerships with immediate partners on ingestion & solution data engineering
• 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.)
• Set the standard for data engineering practices within the company, guiding the architectural approaches, data pipeline designs, and the integration of cutting-edge technologies to foster a culture of innovation and continuous improvement

Requirements:

• Excellent cross-functional communication - the ability to break down complex technical components for technical and non-technical partners alike
• Innate aptitude for interpreting complex datasets with demonstrated ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills. (Healthcare experience preferred)
• 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
• Proven ability to independently handle ambiguous project requirements and lead data initiatives from start to finish, while collaborating extensively with cross-functional, non-technical teams to inform and shape product development
• 5+ 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
• Relevant industry certifications in a variety of Data Architecture services (Databricks Certified Data Engineer Professional, AWS Certified Data Engineer or Solutions Architect Professional, SnowPro® Advanced Architect/Data Engineer, Microsoft Fabric Data Engineer, and dbt Analytics Engineering)
• Experience with MLOps and/or developing and maintaining machine learning models and infrastructure
• Experience with data visualization tools and analytics technologies (Sigma, Looker, Tableau, etc.)
• Degree in Computer Science, Engineering, or related field