You'll use it to turn raw legacy schemas and documentation into first-pass mapping specs, reconcile inconsistent field names and codes across systems, and catch data-quality problems that manual review would miss before they hit production. 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.