Senior Data Engineer
New
Q
QventusHealthcare technology
Remote, United StatesFull-TimeSenior
Salary130,000 - 150,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 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
- Required Skills
- AWSData engineeringData modelingdbtDatabricksMLOpsHIPAA
Requirements
- Design, develop, and optimize reliable, modular, and secure data pipelines.
- Build data foundations for data delivery across applications, analytics, and machine learning.
- Interpret complex datasets, identify patterns and anomalies, and extract meaningful insights.
- Independently manage ambiguous project requirements and lead data initiatives from start to finish.
- Collaborate with cross-functional technical and non-technical partners to inform product development.
- Healthcare experience is preferred.
- 5+ years of experience designing, building, and operating cloud-based data platforms is listed as a bonus qualification.
- Relevant data architecture certifications are a bonus, including Databricks, AWS, SnowPro, Microsoft Fabric, and dbt certifications.
- Experience with MLOps or developing and maintaining machine learning models and infrastructure is a bonus.
- Experience with data visualization tools such as Sigma, Looker, or Tableau is a bonus.
- A degree in Computer Science, Engineering, or a related field is a bonus.
Responsibilities
- Discover, evaluate, and integrate datasets in collaboration with data stakeholders, including pipeline development, data modeling, and documentation.
- Track and maintain context for data assets throughout their lifecycle and partner on ingestion and solution data engineering.
- Translate product and analytical visions into data pipelines that deliver high-quality, trusted data products.
- Design data structures and build and schedule data transformation pipelines.
- Improve transparency across data products and pipelines.
- Guide data engineering architecture, pipeline design, and technology integration.
View Full Description & ApplyYou'll be redirected to the employer's site
