Data Integration Engineer, Clinical Systems

The University of Arizona's Information Technology Services (UITS) invites you to apply to the role of Data Integration Engineer, Clinical Systems.

This position is responsible for the electronic transfer of clinical data and information from Cerner, the Banner Clinical Information system (or Electronic Health Record (EHR) system) to University of Arizona Cancer Center's (UACC) Oncore system (clinical trials management system).

The Data Integration Engineer, Clinical Systems designs, builds, monitors, and maintains data flows from one system to another. This is a key operational role focused on creating an efficient and repeatable process for data exchange between clinical systems. This role reports to the UITS organization, but works with UACC Clinical Trials Office (CTO) leadership to meet their needs.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

• Create and maintain the data pipelines, connections, and technical interfaces that ensures data can be transferred in digital format between different clinical systems in a standardized, scalable, and secure way-critical for efficient support of clinical research.
• Utilize expert knowledge of Applications Development to develop new approaches/solutions to meet business needs.
• Design, develop, configure, test, and deploy APIs and integration interfaces or data transfer methods to move clinical data between the Cerner and Oncore system.
• Work with healthcare interoperability standards such as HL7 FHIR and RESTful APIs.
• Support secure, reliable exchange of clinical data across electronic health records (EHRs), clinical trial systems, and partner platforms.
• Map raw clinical data into consistent, high-quality formats and ensure the data is accurate and usable both in Oncore and other electronic data capture formats used by clinical trial sponsors.
• Map data elements between source and target systems.
• Transform clinical data to meet interoperability and business requirements.
• Validate data for completeness, accuracy, and adherence to healthcare standards. Minimize errors as these affect the quality of patient care, reporting, and compliance.
• Ensure operational reliability and issue resolution with the goal of keeping the data flow without disruptions. Perform proactive monitoring to ensure continuity and system stability.
• Monitor interface queues and data transmission workflows.
• Identify and troubleshoot interface failures, data errors, and performance bottlenecks.
• Resolve integration issues to minimize downtime and data loss.
• Facilitate cross-functional communication and governance to align technical solutions with clinical and regulatory requirements, ensuring clear documentation, reduced risk, and long-term system maintainability.
• Collaborate with clinical teams, physicians, IT stakeholders, and external partners. This includes collaboration across different units and institutions such as Banner University Medical Group, UITS, and UACC.
• Gather and translate clinical and business requirements into technical solutions. Influence non-IT clinicians and stakeholders on feasibility of solution creation and other requirements to meet institutional and compliance requirements.
• Ensure all Protected Health Information (PHI) data integrations meet HIPAA compliance standards, including security, access control, and auditing.
• Maintain interface documentation, configuration specs, and compliance records.
• Additional duties as assigned.

Knowledge, Skills, and Abilities;

• Knowledge of HL7 FHIR and RESTful APIs to support
  secure, standardized data exchange across EHRs and clinical trial systems.
• Knowledge of healthcare data governance, security,
  and regulatory requirements, ensuring secure and compliant data
  exchange.
• Knowledge of clinical trials management systems
  (CTMS), electronic data capture (EDC) platforms, and the clinical research
  data lifecycle.
• Knowledge of ETL (Extract, Transform, Load)
  processes and data pipeline architectures to support systematic data
  extraction, transformation, and loading between clinical systems.
• Knowledge of SQL and database structures to
  support data queries, validation, and interface troubleshooting.
• Knowledge of data privacy and
  security frameworks applicable to clinical research, including HIPAA, IRB
  requirements, and institutional policies governing protected health
  information (PHI).
• Knowledge of AI tools and their application to software development, data integration, and data quality workflow.
• Knowledge of responsible AI use principles
• Skill in designing, developing, testing,
  deploying, and supporting APIs and integration interfaces between systems
  such as Cerner and OnCore.
• Skill in mapping, transforming, and validating
  clinical data to ensure accuracy, standardization, and compliance with
  healthcare requirements.
• Skill in maintaining interface documentation,
  configuration specifications, and compliance records to support governance
  and long-term maintainability.
• Skill in programming and scripting languages
  (e.g., Python, SQL, or similar) to support data pipeline development,
  automation, and transformation logic.
• Skill in data quality assurance methods, including
  completeness checks, referential integrity validation, and error
  reconciliation to ensure transferred clinical data meets both operational
  and regulatory standards for clinical trials.
• Skill in performing root cause analysis for data
  discrepancies, interface failures, and system integration issues using
  systematic troubleshooting methodologies and diagnostic tools.
• Skill in data modeling and data warehousing
  concepts to support complex mapping and transformation requirements.
• Ability to monitor interface workflows,
  troubleshoot integration failures and performance issues, and minimize
  downtime and data loss.
• Ability to collaborate with cross-functional
  stakeholders to translate clinical and business requirements into
  technical integration solutions.
• Ability to adapt to evolving interoperability
  standards, platform updates, and regulatory changes, including evaluating
  and adopting new technologies in a rapidly changing healthcare informatics
  environment.
• Ability to manage multiple concurrent integration
  projects and priorities, balancing operational urgency with long-term
  architectural quality and maintainability.
• Ability to assess and mitigate risks associated
  with data integration, including data loss, latency, format mismatches,
  and compliance violations, employing proactive monitoring and contingency
  planning.
• Ability to embrace and integrate emerging AI technologies as appropriate into daily work practices.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

• Bachelor's degree or equivalent advanced learning attained through professional level experience required.

AND

• Minimum of 5 years of relevant work experience, or equivalent combination of education and work experience.

• Experience with Oracle Cerner EHR system architecture, Cerner Ignite APIs, and/or FHIR-based integrations.
• Experience with OnCore Clinical Trials Management System (CTMS) or similar platforms.
• Experience with HL7 FHIR and healthcare interoperability standards.
• Experience with ETL tools, integration middleware, or interface engines.
• Experience with SQL, Python, or other programming/scripting languages used in data integration.
• Experience in a clinical research, academic medical center, or healthcare environment.
• Experience leveraging AI-assisted tools to enhance productivity across software development, documentation, data integration, and data quality workflows.
• Experience with HIPAA and clinical research regulatory requirements.
• Experience with healthcare terminologies and data standards.