Principal Data Engineer

For more than 45 years, Careington International has been a leader in the health and wellness benefits space. Since its founding in 1979, Careington has been delivering dental discount solutions as its core competency. Today, Careington has expanded to offer a growing portfolio of 150+ health, wellness, lifestyle and virtual health products and services designed to deliver cost savings across a spectrum of life needs. Through its affiliated nationally licensed third-party administrator (TPA), Careington also delivers full-scale administrative services, including customer service, licensed enrollment, claims administration, individual and group billing, and more.

This role will be worked from our Frisco, TX, corporate location on Gaylord Pkwy.

The Principal Data Data Engineer is responsible for designing, building, and optimizing scalable data pipelines and data platforms that support operational processing, analytics, and advanced data science initiatives. This role will focus on developing and maintaining enterprise data integration frameworks that enable efficient ingestion, transformation, and distribution of critical business data including client eligibility, claims, and provider network datasets.

You will play a key role in building and expanding the organization’s Azure-based data platform, including the implementation of a data lake architecture using the medallion data model (Bronze, Silver, Gold). This role will partner with analytics, reporting, and application development teams to ensure reliable data delivery, improved data quality, and scalable infrastructure to support dashboards, artificial intelligence, and machine learning initiatives.

EXPECTED WORK AND PERFORMANCE

• Design, develop, and maintain scalable data pipelines using tools such as SQL Server Integration Services (SSIS), Azure Data Factory, and Python.

• Optimize inbound data ingestion frameworks supporting client eligibility files, claims data, and provider network data from multiple external partners.

• Develop reusable patterns for secure and efficient ingestion of structured and semi-structured data from file transfers, APIs, and other integration methods.

• Design and implement robust data validation, monitoring, and logging frameworks to ensure data integrity and operational visibility.

• Build and maintain data lake architecture within Azure following the medallion design pattern (Bronze, Silver, Gold layers).

• Develop transformation processes to standardize, cleanse, and prepare enterprise datasets for reporting, analytics, and downstream application consumption.

• Collaborate with analytics and reporting to deliver curated datasets supporting dashboards, AI, and machine learning models.