Senior Data Integration Engineer

** We are currently not accepting resumes from ANY third party vendors. Please do not inquire.** Senior Data Integration Engineer - Contract to Hire Position Summary We are seeking a Data Integration Engineer to connect complex Practice Management (PM) systems to a central AI platform. You will turn legacy schemas and documentation into source-to-target mapping specifications, reconcile inconsistent fields and codes, and identify data quality issues before they reach production. This role requires someone who can work through poorly documented systems, use AI tools thoughtfully to accelerate analysis, and build reliable integrations.

Key Responsibilities

Partner with the AI Architect to design integration approaches for internal and external systems. Use AI and LLM tools to accelerate schema analysis, field mapping, code reconciliation, and data quality checks. Validate the results before implementation. Create data models and source-to-target mapping specifications for PM system data. Build and maintain ETL pipelines and REST or SOAP integrations that transform source data into the platform’s target format. Cleanse, structure, and enrich data from legacy systems, including systems with limited documentation. Monitor production integrations, troubleshoot failures, and resolve data quality issues. Maintain clear documentation for data models, mapping decisions, and pipeline configurations. Work with product, engineering, operations, and leadership to clarify requirements and resolve integration challenges.

Qualifications

At least 5 years of experience in data integration, systems integration, or ETL engineering, including production integrations with complex legacy systems. Strong SQL skills and experience working with relational databases. Experience designing data models, writing mapping specifications, and building ETL pipelines and APIs. Hands-on experience using AI or LLM tools for tasks such as schema inference, field mapping, entity resolution, or automated data quality checks. Be prepared to discuss specific examples and how you validated the output. Working knowledge of Python, JavaScript, or a similar scripting language. Experience with REST and SOAP APIs and common data formats, including JSON, XML, CSV, flat files, and EDI. Understanding of HIPAA requirements and practices for protecting PHI. Preferred Experience Healthcare or revenue cycle management experience, particularly with one or more Practice Management systems. Experience with Azure integration tools such as Fabric, Data Lake, Azure SQL, or Data Factory. Familiarity with HL7 or FHIR.