Senior Director, Data Architecture

At the company, our work helps hospitals recover the revenue they've earned so they can continue serving patients and communities. Trusted by more than 1,300 hospitals across 48 states, we combine specialized expertise with proprietary technology to solve problems others can't. Just as importantly, we've built a workplace where people support one another, embrace innovation, and are trusted to do their best work.

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We are hiring a Senior Director of Enterprise Data Architecture & Standards to bring order and shared meaning to data that today lives across Customer Success, Finance, Data Science, Engineering, and Operations. With most of our enterprise data now consolidated in Snowflake, the opportunity — and the challenge — is no longer access to data, but agreement on what it means. This role owns that problem end to end: establishing enterprise data standards, a data catalog, and a business ontology so that every team, from an embedded analyst in Finance to a data scientist modeling patient financial outcomes, is working from the same definitions, the same lineage, and the same source of truth.

This is a hands-on architecture role, not a management position. You will spend most of your time in Snowflake, in data models, in cataloging tools, and in working sessions with stakeholders — not building a team beneath you. You will report to the SVP of AI, Data & Data Science and operate as the senior-most technical authority on data standards, taxonomy, and governance across the enterprise.

What You'll Do

• Establish enterprise data standards — Design and drive adoption of an enterprise data standards program covering naming conventions, business/technical metadata, data quality rules, and reporting definitions across the Snowflake data warehouse.

• Build and own the data catalog — Select, implement, or extend a data catalog that makes data discoverable and trustworthy, with clear ownership, definitions, sensitivity classifications, and usage guidance for every core data asset.

• Define a common language, grounded in healthcare context — Develop a shared ontology and enterprise data dictionary that reconciles how Customer Success, Finance, Data Science, Engineering, and Operations each define core entities and metrics (e.g., "claim," "account," "client," "revenue recognized"), applying working knowledge of healthcare revenue cycle, claims, patient financial, and provider/payer data to ensure definitions reflect the realities of the business.

• Establish lineage and reporting standards — Define and implement data lineage standards so any consumer can trace a metric or field from source to consumption, while partnering with embedded analytics teams in Data Science, Operations, and Finance to align reporting definitions and move toward a single set of certified reports and semantic models.

• Architect hands-on — Serve as the enterprise data architect for how data is modeled, organized, and governed within Snowflake, working directly alongside data engineering on schema design, domain modeling, and platform architecture decisions.

• Drive cross-functional alignment and sustainable governance — Act as the connective tissue between technical teams and business stakeholders, translating between business concepts and data models, and establishing decision rights, change-management processes, and governance forums (e.g., a data council) so standards remain living, adopted practices.

What You Bring

• 10+ years in data architecture, data management, or enterprise data roles, including direct, hands-on experience building or scaling data catalogs, data dictionaries, taxonomies, or ontologies across a complex organization.

• Deep hands-on platform and tooling experience — Snowflake (or a comparable cloud data warehouse) including data modeling, schema design, and architecture tradeoffs, plus direct experience with data cataloging/metadata management tools (e.g., Snowflake Horizon, Collibra, Alation, Atlan, DataHub, Purview) and, integration of legacy data sources (e.g. RDBMS) lineage tooling and practices.

• Proven ability to build enterprise-wide agreement through influence — a track record of aligning functions with genuinely different vocabularies and incentives (Finance, Data Science, Operations, Customer Success, Engineering), backed by strong written and verbal communication skills and the ability to facilitate consensus among stakeholders who don't naturally agree.

• Healthcare domain experience — ideally within the healthcare revenue cycle, payer/provider, or patient financial services lifecycle, with comfort in clinical, claims, or billing data concepts.

• Strong technical foundations as a senior IC architect — solid data modeling fundamentals (dimensional modeling, entity-relationship modeling, semantic layers), familiarity with modern data stack components (ELT/ETL, orchestration, BI/semantic tools like dbt, Looker, Power BI, or Tableau), and a track record operating hands-on at a senior individual-contributor level while also representing data architecture in leadership forums.

Nice to Have

• Experience with data governance frameworks (e.g., DAMA-DMBOK) and formal data stewardship programs.

• Familiarity with healthcare data standards (e.g., X12, HL7/FHIR, CPT/ICD coding) and regulatory considerations (HIPAA) as they relate to data classification and access.

• Experience introducing or scaling ontology/knowledge-graph approaches to support AI and data science initiatives.

What Success Looks Like

• Common definitions, one source of truth — A published, adopted enterprise data dictionary and ontology, with core business entities and metrics defined once and referenced consistently across Finance, Customer Success, Data Science, Operations, and Engineering.

• A functioning data catalog — A live data catalog covering the highest-value Snowflake datasets, with owners, definitions, and lineage documented and kept current.

• Traceable lineage — Documented lineage for key reporting metrics from source system to consumption, reducing time spent reconciling conflicting numbers across teams.

• Aligned reporting — A reduced number of duplicate or conflicting reports and metric definitions, with embedded analytics teams operating from shared, certified data models.

• Durable governance — A governance structure (council, stewardship roles, or equivalent) that stakeholders across the business recognize and actively participate in.

Work at Home Requirements

• A quiet, distraction-free environment to work from in your home.

• A secure internet connection is required.

• Home internet with speeds >20 Mbps for downloads and >10 Mbps for uploads.

• The workspace area accommodates all workstation equipment and related materials and provides adequate surface area to be productive.

Must reside in the United States within one of the states listed below:

Alabama, Arkansas, Delaware, Florida, Georgia, Illinois, Iowa, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Maine, Michigan, Minnesota, Missouri, Mississippi, North Carolina, Nebraska, New Hampshire, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota (CST Time Zone), Tennessee, Texas (CST Time Zone), Vermont, Virginia, Wisconsin, and West Virginia

The company is an Affirmative Action/Equal Opportunity Employer committed to providing equal employment opportunities for all applicants and employees. We make employment decisions without regard to any characteristic protected by applicable law and encourage individuals of all backgrounds to apply.

Employment is contingent upon eligibility to work in the United States, verification of employment history, and successful completion of a background check.