Qventus
Senior Data Engineer
Vaga remota de Senior Data Engineer com fit claro de localização do candidato.
Publicada2 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Estados Unidos
Resumo da vaga
Senior Data Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Key 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.
What We’re Looking For
- 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.
Bonus Points For
- 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
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