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AI Data Integration Engineer, RCM Systems

Harris Computer
Oklahoma, USA
Full-time
Mid · 5+ years experience
Onsite
Discovered 3 weeks ago
azurejavascriptopenaipythonsql

Full Job Posting

Key Responsibilities

  • Lead the architectural design of integration strategies and solutions that connect various internal and external systems to our central platform.
  • AI-accelerated mapping & data quality: use AI/LLM tools to speed up schema mapping, field reconciliation, and anomaly detection.
  • Data modeling & mapping: build data models and source-to-target mapping specs from Practice Management (PM) systems to our AI platform.
  • Pipelines: design and build ETL processes and REST/SOAP APIs that move data into Resolv Core, per the architect's design.
  • Data wrangling: cleanse, structure, and enrich source data into Resolv Core's target format.
  • Pave the path where there's no existing playbook; several of these legacy systems are poorly documented.
  • Reliability: monitor, troubleshoot, and resolve integration issues in production.
  • Collaboration: work closely with our AI Architect, product, engineering, operations, and leadership.
  • Documentation: maintain data models, mapping specs, and pipeline configurations.

Qualifications

  • Experience: A minimum of 5 years in data/system integration or ETL engineering, building production integrations against complex legacy systems.
  • Healthcare/RCM experience preferred; direct exposure to one or more Practice Managenent (PM) systems.
  • Technical (AI first):
  • Hands-on experience using AI/LLM APIs (e.g., OpenAI, Azure OpenAI) for schema inference, field-mapping/entity resolution, or automated data-quality checks — with concrete examples.
  • Judgment on the best approach to using AI tooling.
  • Production-grade proficiency with SQL and experience with relational databases.
  • Familiarity with Python and JavaScript (or similar scripting language).
  • Design, build, and maintain ETL processes, data pipelines, and APIs to facilitate the seamless flow of data between different applications and data sources.
  • REST and SOAP API development.
  • Comfortable with JSON, XML, CSV, flat-file, and EDI formats.
  • Data modeling and mapping-spec authorship.
  • Understanding of HIPAA and PHI security practices.
  • Cloud integration platforms; Azure stack (Fabric, Data Lake, SQL, Data Factory) a plus.
  • HL7/FHIR knowledge.
  • A minimum of 5 years in data/system integration or ETL engineering, building production integrations against complex legacy systems.

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