{"id":1745160,"url":"https://alion.io/job/harris-computer-ai-data-integration-engineer-rcm-systems","title":"AI Data Integration Engineer, RCM Systems","company":{"id":2223,"name":"Harris Computer","domain":"harriscomputer.com","url":"https://alion.io/company/harris-computer","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":37,"ghost_share":0,"stale_share":0.838,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-11-03T05:54:40Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":160000,"currency":"USD","period":"year","gross":null,"usd_annual":160000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FHIR","optional":false},{"name":"HIPAA","optional":false},{"name":"HL7","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SOAP","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-02T00:00:00Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-03T21:35:59Z","board_verified":true,"closed_at":null,"days_open":33,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":32},"description":"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.\nKey Responsibilities\nLead the architectural design of integration strategies and solutions that connect various internal and external systems to our central platform.\nAI-accelerated mapping & data quality: use AI/LLM tools to speed up schema mapping, field reconciliation, and anomaly detection.\n Data modeling & mapping: build data models and source-to-target mapping specs from Practice Management (PM) systems to our AI platform.\nPipelines: design and build ETL processes and REST/SOAP APIs that move data into Resolv Core, per the architect's design.\nData wrangling: cleanse, structure, and enrich source data into Resolv Core's target format.\nPave the path where there's no existing playbook; several of these legacy systems are poorly documented.\nReliability: monitor, troubleshoot, and resolve integration issues in production.\nCollaboration: work closely with our AI Architect, product, engineering, operations, and leadership.\nDocumentation: maintain data models, mapping specs, and pipeline configurations.\nQualifications\nExperience: A minimum of 5 years in data/system integration or ETL engineering, building production integrations against complex legacy systems.\nHealthcare/RCM experience preferred; direct exposure to one or more Practice Managenent (PM) systems.\nTechnical (AI first):\nHands-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.\nJudgment on the best approach to using AI tooling.\nProduction-grade proficiency with SQL and experience with relational databases.\nFamiliarity with Python and JavaScript (or similar scripting language).\nDesign, build, and maintain ETL processes, data pipelines, and APIs to facilitate the seamless flow of data between different applications and data sources.\nREST and SOAP API development.\nComfortable with JSON, XML, CSV, flat-file, and EDI formats.\nData modeling and mapping-spec authorship.\nUnderstanding of HIPAA and PHI security practices.\nCloud integration platforms; Azure stack (Fabric, Data Lake, SQL, Data Factory) a plus.\nHL7/FHIR knowledge.\nThe potential salary range for this role is $150,000.00 USD to $160,000.00 per year. Final compensation will be based on experience, skills, market conditions, and internal equity. 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