Athena Architect

Chartis

30d•$55 - $60•Remote

About The Position

We are seeking an experienced Athena Data Architect with deep expertise in Athena data structures and strong experience mapping healthcare data to the OMOP Common Data Model (CDM). This role will drive the design, transformation, and alignment of Athena data for advanced analytics and reporting, with a focus on clinical and revenue cycle domains.

Requirements

5+ years of experience in healthcare data architecture or data engineering.
Deep hands-on experience with Athena (athenahealth) data models and extracts.
Proven experience implementing or supporting the OMOP Common Data Model (CDM).
Strong experience with data mapping, transformation, and normalization.
Proficiency in SQL and experience with ETL/ELT tools (e.g., Informatica, dbt, Talend, Azure Data Factory, etc.).
Solid understanding of clinical data (EHR) and/or revenue cycle data (RCM).
Experience working with healthcare data standards and vocabularies.
Strong analytical and problem-solving skills.

Nice To Haves

Experience with OHDSI tools and ecosystem.
Familiarity with FHIR, HL7, or other interoperability standards.
Experience with cloud platforms (AWS, Azure, GCP).
Background in healthcare analytics or reporting environments.
Exposure to value-based care or population health analytics.

Responsibilities

Lead the end-to-end data architecture and modeling for Athena (athenahealth) data.
Drive the mapping and transformation of Athena data into the OMOP Common Data Model (CDM) to support analytics and reporting use cases.
Collaborate with clinical, revenue cycle, and analytics stakeholders to define data requirements and reporting needs.
Design and implement ETL/ELT pipelines to standardize and load data into OMOP-compliant structures.
Ensure data quality, integrity, and consistency across clinical and financial datasets.
Translate complex healthcare workflows (clinical + revenue cycle) into scalable data models.
Provide expertise in healthcare data standards, vocabularies, and terminologies (e.g., SNOMED, ICD, CPT, LOINC).
Partner with data engineers, analysts, and BI teams to enable downstream reporting and analytics.
Document data mappings, lineage, and architecture for governance and compliance.
Support performance tuning and optimization of large healthcare datasets.