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.
- Design scalable frameworks for both inbound and outbound data integrations to support new client onboarding and enterprise data exchange requirements.
- Monitor and tune data pipeline performance to ensure efficient data movement, minimal latency, and reliable execution.
- Implement data governance, metadata management, and data lineage practices to improve transparency and trust in enterprise data assets.
- Participate in architectural discussions and recommend improvements to data infrastructure, tools, and processes to support enterprise data strategy.
- Provide mentorship and technical guidance to junior data engineers and developers.
- Collaborate with cross-functional teams including database administrators, application developers, infrastructure teams, and business stakeholders to support enterprise data initiatives.
QUALIFICATIONS
Required
- Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field.
- 10+ years of experience in data engineering, data integration, or related roles.
- Strong experience building ETL/ELT pipelines using SSIS, Azure Data Factory, or similar integration platforms.
- Experience with Python for data processing, automation, or pipeline orchestration.
- Strong experience working with SQL Server and relational databases.
- Experience designing scalable data ingestion and transformation processes for large datasets.
- Experience building or supporting cloud-based data platforms within Microsoft Azure.
Preferred
- Experience designing and implementing data lake architectures.
- Experience with medallion data architecture (Bronze, Silver, Gold).
- Experience supporting analytics platforms such as Power BI or similar BI tools.
- Experience with distributed data processing or big data technologies.
- Experience supporting AI/ML data pipelines and analytics workloads.
- Experience with healthcare, insurance, or large-scale transactional data environments.
SKILLS
- Strong problem-solving and analytical thinking abilities.
- Ability to design scalable, maintainable, and reusable data integration frameworks.
- Strong communication skills with the ability to explain complex technical concepts to technical and non-technical stakeholders.
- Experience collaborating with cross-functional teams including data analysts, data scientists, application developers, and infrastructure engineers.
- Ability to manage multiple priorities in a fast-paced environment.
- Strong attention to detail and commitment to data quality and operational reliability.
- Ability to mentor and provide technical leadership within a data engineering team.