Senior Data Platform Engineer

Qventus is leading the transformation of healthcare through innovative solutions that harness machine learning, generative AI, and behavioral science. As a Senior Data Platform Engineer, you will drive the strategic evolution and design of data platform investments and pipelines, ensuring scalability and reliability while collaborating with cross-functional teams to translate needs into technical solutions.

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
• Support production ML Ops functionality and advance the quality of our core ML & LLM platform capabilities
• Partner strategically with data science, analytics, and data engineering leads and Architects to gather feedback and drive the development of scalable platform solutions that unlock new features within the defined architectural framework
• Provide expertise on the overall data engineering best practices, standards, architectural approaches and complex technical resolutions
• 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.)

Requirements:

• Strong cross-functional communication - ability to break down complex technical components for technical and non-technical partners alike
• 4+ years of hands-on 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
• 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)
• Experience working with Databricks and deployed production grade pipelines
• Python and DBT SQL
• Proficiency in interpreting complex datasets, including the ability to discern underlying patterns, identify anomalies, and extract meaningful insights, demonstrating advanced data intuition and analytical skills with the ability to translate these insights into recommendations for platform improvements that align with the overall architecture
• Relevant industry certifications in various 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 (Sigma, Looker, PowerBI, etc.)
• Degree in Computer Science, Engineering, or related field
• Experience working with healthcare data and HIPAA data protection