Senior Data Engineer

1 month ago

Chicago, United States TAG - The Aspen Group Full time

The Aspen Group (TAG) is one of the largest and most trusted retail healthcare business support organizations in the U.S. and has supported over 20,000 healthcare professionals and team members at more than 1,300 health and wellness offices across 48 states in four distinct categories: dental care, urgent care, medical aesthetics, and animal health. Working in partnership with independent practice owners and clinicians, the team is united by a single purpose: to prove that healthcare can be better and smarter for everyone. TAG provides a comprehensive suite of centralized business support services that power the impact of five consumer-facing businesses: Aspen Dental, ClearChoice Dental Implant Centers, WellNow Urgent Care, Chapter Aesthetic Studio, and AZPetVet. Each brand has access to a deep community of experts, tools and resources to grow their practices, and an unwavering commitment to delivering high-quality consumer healthcare experiences at scale.


Our continued growth has created an opportunity to join our IT team as a Senior Data Engineer.


As a Senior Data Engineer, you will play a pivotal role in modernizing our EPMS systems at Aspen Dental. You will collaborate with other data engineers and software engineers to revamp our legacy systems by leveraging cutting-edge cloud-native technologies from Google Cloud Platform (GCP). Our tech stack uses Microsoft .NET (7), Python, Airflow, Microservice-based architecture, and advanced SQL and NoSQL data layers on Kubernetes operating as an active-active HA multi-region solution.


Responsibilities:

  • Data Architecture & Modeling: Collaborate with cross-functional teams to define data, modeling, and reporting requirements, and design data product architectures.
  • Data Pipeline Development: Design and implement scalable data pipelines using Python, GCP DataFlow, Cloud Functions, and/or FastAPI, and utilize orchestration tools like Airflow and Prefect.
  • ETL Strategy: Architect and develop efficient ETL solutions, ensuring they are reliable, secure, and scalable within a cloud-native environment.
  • Machine Learning Integration: Operationalize and integrate machine learning models into existing systems, develop model pipelines, and build standardized modules to support data scientists.
  • Infrastructure & Testing: Configure infrastructure for deploying data solutions, conduct automated testing for continuous delivery, and contribute to the development of an MLOps framework.
  • Mentorship: Guide and mentor junior data engineers, fostering best practices and a collaborative environment.
  • Data Pipeline Development: Design and implement scalable data pipelines using Python, GCP DataFlow, Cloud Functions, and/or FastAPI, and utilize orchestration tools like Airflow and Prefect.


Qualifications:

  • Bachelor’s Degree (or foreign equivalent) in Data Science, Mathematics or related data.
  • Preferred: Master’s Degree (or foreign equivalent) in Data Science, Mathematics or related data or computational social or hard science field and 5 years of experience in IT, Analytics and/or Data Science including:
  • 5 years programming and maintaining SQL code
  • 5 years programming in Python or similar OOP languages
  • years creating data pipelines
  • year maintaining monitoring for data pipelines
  • years developing reporting dashboard
  • 2 years developing and operationalizing machine learning model
  • 2 years working with cloud platforms such as Google Cloud Platform (GCP)
  • 2 years deploying containerized solutions



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