Senior Data Integration Engineer

Pinnacle Consulting & Recruitment; Detroit (MI); On-site; USD 105,000 - 145,000; Full time

Job summary

Pinnacle Consulting & Recruitment seeks an AI Data Integration Engineer to migrate legacy healthcare data to a next-generation platform. You will design data models, mappings, and pipelines, using AI/LLM tooling to accelerate schema analysis and data-quality checks.

You’ll work with an AI Architect and collaborate with product and engineering teams to ensure robust, scalable integrations across RCM and Practice Management systems. This is a contract-to-hire role based in Detroit, MI.

Qualifications

• 5+ years of experience in data integration, ETL, or systems integration.
• Experience building production integrations with legacy systems.
• Hands-on with AI/LLM APIs for schema inference, mapping, or data quality analysis.

Responsibilities

• Design integration solutions connecting internal and external systems to a centralized healthcare technology platform.
• Leverage AI/LLM tools to accelerate schema analysis, field mapping, and entity resolution.
• Create source-to-target mappings for legacy Practice Management and RCM systems.
• Develop and maintain ETL processes, data pipelines, and REST/SOAP API integrations.
• Extract, cleanse, structure, transform, and enrich legacy data for the target platform.
• Document data models, mapping specs, and transformation rules clearly.
• Monitor integrations, troubleshoot failures, and resolve data-quality issues.

Skills

Data integration

ETL engineering

SQL

API integrations

AI/LLM tooling

Tools

Azure Data Factory

Databricks

OpenAI API

Job description

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

AI Data Integration Engineer

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.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.