Healthcare Data Architect

Empower is a high-growth, innovation-driven company focused on delivering impactful solutions that transform how healthcare organizations operate. Our team combines deep industry expertise with a commitment to excellence, enabling us to solve complex challenges at scale. We foster a collaborative, results-oriented culture where high performers thrive, ideas are valued, and continuous improvement is expected. We move quickly, think strategically, and hold a high bar for performance, while supporting each other in achieving ambitious goals.

If you care about building a data foundation that powers real-time ML predictions, enjoy working at the intersection of data architecture, performance engineering, and healthcare interoperability, and want your work to have a direct impact on patient care, you will feel at home here.

Summary of Role

We are seeking an experienced Healthcare Data Architect to join the Empower Healthcare team. Preference will be given to candidates with prior experience working directly for Epic, given the depth of platform knowledge that brings to designing and optimizing our data environment.

We are not an EHR. We currently consume Epic-sourced clinical data through Snowflake, our data warehouse, and use it to power ML models whose outputs are displayed to end users in near real time. Live integration with EHR/FHIR APIs directly is on our near-term roadmap. This role owns the architecture connecting those data sources to fast, reliable predictions our users can act on.

This is not a general software engineering role. It requires deep, demonstrable expertise in healthcare data architecture, Snowflake performance engineering, and low-latency data serving. Candidates should expect technical questions that go well beyond surface familiarity, and applicants without direct, verifiable experience in this domain will not be considered.

This is an immediate need and we are actively hiring. The interview process includes an intro call, behavioral interview, a technical interview administered by the Engineering Manager, and a final interview with Senior Leadership.

Responsibilities

• Architect the data layer connecting Snowflake to the application, optimized for low-latency retrieval at inference time.
• Design data models, indexes, and query patterns that support real-time and near-real-time ML inference.
• Partner with the ML team on feature pipelines and serving architecture (feature stores, caching, precomputation) to meet strict latency requirements.
• Own Snowflake performance tuning for high-throughput, low-latency application queries.
• Build and maintain ETL/ELT pipelines moving Epic-sourced data from Snowflake into structures suited for ML consumption.
• Design and lead upcoming live integrations with EHR/FHIR APIs (SMART on FHIR, HL7), building on the current Snowflake-based pipeline.
• Define APIs/interfaces with application engineers for serving model outputs to the UI.
• Establish and enforce data governance, data quality, and security standards across the data environment.
• Ensure architecture and data practices comply with HIPAA and other applicable healthcare regulations.
• Document technical decisions and contribute to internal runbooks and data architecture standards.

Must Have

Data architecture:

• 5+ years of experience in data architecture, data modeling, or data warehousing, with a strong focus on healthcare data.
• Working knowledge of Epic data models (Clarity/Caboodle) sufficient to work effectively with Epic-sourced data.
• Demonstrated experience designing low-latency data serving layers for application or ML consumption, not just batch reporting.

Interoperability:

Experience with HL7 and FHIR (R4), including SMART on FHIR app integration and OAuth 2.0-based authorization flows, and the ability to lead a future live EHR/FHIR integration effort.

Data engineering:

Strong SQL skills and experience building and maintaining ETL/ELT pipelines.

Nice to Have

Performance and ML serving:

Direct, hands-on experience with Snowflake, including query and warehouse performance tuning for high-throughput, low-latency workloads.
Experience feeding data to production ML models and serving predictions to end users quickly (caching, precomputation, feature stores, or similar techniques

• Prior direct employment at Epic Systems, or Epic certification (Clarity or Caboodle).
• Experience with Snowpark or other Snowflake-native processing tools.
• Experience with real-time feature stores (e.g., Feast, Tecton) or caching layers (e.g., Redis) for ML serving.
• Security and compliance:
• Deep knowledge of HIPAA and healthcare data governance requirements.
• Experience implementing data security controls, including access management and audit logging.
• Experience with population health data, value-based care models, or risk scoring (e.g., HCC, RAF).
• Master's degree in data science, computer science, or a related field.

Technology Stack (Relevant to This Role)

Data platform

• Snowflake (connector, Snowpark), PostgreSQL EHR / Interoperability
• Epic Clarity, Epic Caboodle, FHIR R4, SMART on FHIR OAuth, HL7 (upcoming live integration) ML serving
• Feature stores, caching layers, low-latency query design Data engineering
• SQL, ETL/ELT pipelines, data modeling and warehousing tools Auth / Security
• OAuth 2.0, HashiCorp Vault, audit logging, HIPAA-aligned access controls Infra / Tooling
• Git, GitHub, CI/CD (e.g., GitHub Actions), Docker

Qualifications

• Bachelor's degree in Computer Science, Data Science, or a related field, OR equivalent experience.
• 5+ years of professional experience in data architecture, with direct experience in healthcare data environments.
• Clear communication skills and the ability to translate complex technical concepts for non-technical stakeholders.
• Comfort working in a healthcare/regulated context where accuracy, security, and compliance matter.
• Eligible to work in the United States and currently reside in United States.
• Pass stringent background checks pertinent to the healthcare industry (Identity Verification, Criminal Check, OIG / SAM, FACIS L3) and a pre-employment drug test.
• Discipline to work in a fully remote environment while staying on task and engaged.