Senior Data Integration Engineer

This is a contract-to-hire position. We are not accepting resumes from third party vendors.

We are seeking an AI Data Integration Engineer to support a healthcare technology company’s migration from multiple legacy revenue cycle management and Practice Management systems to a next-generation platform.

This individual will build the data models, source-to-target mappings, pipelines, and data-quality controls needed to migrate complex legacy data into the new platform. You will work closely with an AI Architect and execute against the broader architecture and integration strategy.

AI and LLM tooling will be central to this role. You will use these tools to analyze legacy schemas and documentation, generate first-pass mapping specifications, reconcile inconsistent field names and codes, and identify data-quality issues before they reach production.

• Design and implement integration solutions connecting internal and external systems to a centralized healthcare technology platform.
• Use AI and LLM tools to accelerate schema analysis, field mapping, entity resolution, code reconciliation, and anomaly detection.
• Build data models and detailed source-to-target mapping specifications for legacy Practice Management and RCM systems.
• Design, build, and maintain ETL processes, data pipelines, and REST or SOAP API integrations.
• Extract, cleanse, structure, transform, and enrich legacy data into the target platform’s required format.
• Work through poorly documented systems and establish repeatable integration and mapping processes where no formal playbook exists.
• Develop and execute data-quality checks to validate completeness, accuracy, consistency, and integrity.
• Monitor production integrations, troubleshoot failures, and resolve pipeline and data-quality issues.
• Partner with the AI Architect, product, engineering, operations, and leadership teams.
• Maintain clear documentation for data models, mapping specifications, transformation rules, and pipeline configurations.

• At least 5 years of experience in data integration, systems integration, or ETL engineering.
• Experience building and supporting production integrations involving complex or poorly documented legacy systems.
• Hands-on experience using AI or LLM APIs, such as OpenAI or Azure OpenAI, for schema inference, field mapping, entity resolution, or automated data-quality analysis.
• Strong judgment regarding where AI tools can improve integration work and where human validation is required.
• Production-level SQL skills and experience working with relational databases.
• Experience designing and maintaining ETL processes, data pipelines, and system integrations.
• Experience developing or consuming REST and SOAP APIs.
• Ability to work with JSON, XML, CSV, flat-file, and EDI formats.
• Experience with data modeling and source-to-target mapping-specification development.
• Ability to work independently, investigate unfamiliar systems, and create structure within ambiguous environments.

• Healthcare technology, revenue cycle management, or Practice Management system experience.
• Understanding of HIPAA requirements and PHI security practices.
• Experience with Azure technologies such as Fabric, Data Lake, Azure SQL, Data Factory, or Databricks.