Data Engineer Architect Jobs in Tennessee (NOW HIRING)

This is OUR story... and YOUR next chapterAt HCA Healthcare, our Digital Transformation and Innovation (DT&I) team is redefining what’s possible inpatient care. By leveraging the power of artificial intelligence, automation, and digital technologies, DT&I is helping drive meaningful improvements in clinical outcomes, reduce manual workload, and expand the reach of our care teams. If you're passionate about using technology to improve human life, this is where your work truly matters

What you will accomplish in this role Job Summary and Qualifications

The Staff Data Engineer serves as a technical leader within the Data Sourcing team, responsible for the design, development, testing, implementation, documentation, and maintenance of enterprise data integration and cloud modernization solutions supporting the HCA Data Office. This role enables the secure, scalable, and reliable movement of healthcare data from Electronic Health Record (EHR) systems and other source applications to enterprise consumers across the organization.

The position supports both existing data integration platforms—including SQL Server Integration Services (SSIS), Microsoft SQL Server, and PostgreSQL—and the strategic modernization of these solutions to Google Cloud Platform (GCP). The Staff Data Engineer will define architecture standards, migration strategies, and operational best practices while leading the evolution of HCA's next-generation cloud data platform.

Working closely with business, analytics, engineering, architecture, and operational teams, this individual will provide hands-on technical leadership, solve complex data engineering challenges, mentor team members, and drive adoption of modern engineering practices including CI/CD, automated testing, observability, Infrastructure as Code, and cloud-native data solutions

What you will do:

Data Engineering & Integration

• Design, develop, and maintain enterprise data integration solutions supporting healthcare and business data domains.
• Build and optimize ETL/ELT pipelines using SSIS, SQL Server, PostgreSQL, and cloud-native technologies.
• Support ingestion, transformation, validation, and delivery of data from EHR systems and other operational platforms.
• Develop scalable data models and integration patterns that support downstream analytics, reporting, operational, and regulatory use cases.
• Ensure data quality, integrity, lineage, and compliance across all data movement processes.
• Participate in on-call support rotation.

Cloud Modernization & Architecture

• Lead modernization initiatives that migrate legacy data pipelines and workloads from on-premises platforms to Google Cloud Platform (GCP).
• Design cloud-native solutions utilizing BigQuery, Cloud Storage, Dataflow, Cloud Composer, Pub/Sub, Cloud SQL, and related GCP services.
• Define migration strategies, reference architectures, and engineering standards for enterprise-scale data platforms.
• Evaluate new technologies and recommend solutions that improve scalability, performance, reliability, and maintainability.

Technical Leadership

• Serve as a technical mentor and subject matter expert for Data Engineers within Data Source team.
• Lead design reviews, code reviews, and architecture discussions.
• Establish engineering best practices for source control, CI/CD, testing, deployment automation, monitoring, and operational support.
• Collaborate with architects, product owners, and business stakeholders to align technical solutions with strategic objectives.

Healthcare Data Expertise

• Partner with source system teams to understand and integrate data from EHR platforms such as Cerner, Epic, Meditech, and other healthcare applications.
• Support healthcare interoperability and data exchange initiatives involving HL7, FHIR, CCD, X12, or related standards.
• Ensure compliance with HIPAA, security, privacy, and governance requirements for protected healthcare information.

What you will need to have:

Required

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field; equivalent experience may be substituted.
• 7 years of experience in Data Engineering, Data Integration, Data Warehousing, or related disciplines.
• Advanced experience with Microsoft SQL Server and T-SQL development.
• Advanced experience developing and supporting ETL solutions using SSIS or comparable enterprise integration platforms.
• Experience with PostgreSQL database development and optimization.
• Experience designing and supporting large-scale enterprise data pipelines.
• Experience designing, developing, and deploying cloud-based data solutions on Google Cloud Platform (GCP).
• Hands-on experience with one or more GCP data services including BigQuery, Cloud Storage, Dataflow, Cloud Composer, Pub/Sub, Dataproc, or Cloud SQL.
• Experience leading cloud migration, modernization, or transformation initiatives from on-premises platforms to cloud environments.
• Experience leading technical initiatives and mentoring engineering teams.

Preferred

• Experience working with healthcare data and Electronic Health Record (EHR) platforms including Cerner, Epic, and/or Meditech.
• Meditech Data Repository (DR).
• Experience with healthcare interoperability standards such as HL7, FHIR, CCD.
• Experience implementing DataOps, DevOps, CI/CD, Infrastructure as Code (Terraform), and automated testing practices.
• Experience building data products and data platforms in regulated environments such as healthcare, finance, or insurance.
• Google Cloud Professional Data Engineer certification or equivalent cloud certification.

"There is so much good to do in the world and so many different ways to do it."- Dr. Thomas Frist, Sr.
HCA Healthcare Co-Founder

If you find this opportunity compelling, we encourage you to apply for our Staff Data Engineer opening. We promptly review all applications. Highly qualified candidates will be directly contacted by a member of our team.We are interviewing apply today!

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.