Location: In-person / Hybrid — Airmont, NY / Greater Lakewood, NJ Area
About Empeon
Empeon is the modern HCM platform built for healthcare. We power payroll, scheduling, HR, benefits, and compliance for skilled nursing facilities, home care agencies, and other healthcare employers across the country.
Reporting and analytics is a major area of investment for us, and we are looking for a Data Architect to help design the data foundation behind our next-generation reporting and analytics platform.
About the Role
We are looking for a Senior Data Architect to design the data architecture behind Empeon’s reporting and analytics platform. In this role, you will help shape the semantic layer, data models, reporting structures, performance strategy, and security model needed to support scalable self-service reporting and analytics.
The data foundation must be designed so future AI-assisted reporting, natural language queries, intelligent insights, and anomaly detection can be built on top of clean, well-modeled, secure, and trusted data.
This is a senior, hands-on architecture role for someone who understands complex data, can translate business needs into scalable data structures, and can partner closely with engineering and product teams to deliver a strong reporting foundation.
What You'll Do
- Design the data architecture behind a self-service reporting and analytics platform where customers can pull data from across the Empeon platform, combine fields, define calculations, and analyze results.
- Design the semantic layer that turns Empeon’s underlying data model into clean, consistent, business-friendly fields, metrics, and definitions.
- Create scalable data models that support reporting, analytics, dashboards, exports, formulas, derived fields, and reusable metrics.
- Define the architecture for analytics workloads, including how they are separated from transactional systems through read replicas, warehouse layers, materialized views, aggregates, or similar approaches.
- Design secure, multi-tenant data access patterns so customers only see the data they are entitled to access.
- Partner with engineering and product leadership on architecture decisions, including build-vs-buy recommendations for reporting and analytics infrastructure.
- Help define the data structures, metadata, and calculation framework needed to support formulas, derived fields, and reusable reporting logic.
- Establish standards for data quality, metric consistency, naming conventions, lineage, documentation, and governance.
- Work closely with product managers, developers, QA, and business stakeholders to translate reporting and analytics needs into clear technical designs.
- Ensure the data architecture is AI-ready, enabling future use cases such as natural language reporting, AI-assisted report authoring, anomaly detection, and intelligent insights.
What We're Looking For
- 6+ years of experience in data architecture, data engineering, BI architecture, analytics platforms, reporting infrastructure, or similar areas.
- Deep experience designing data models, semantic layers, reporting structures, or BI platforms, whether homegrown or built on tools such as Cube, Looker, dbt, Metabase, Power BI, or similar platforms.
- Strong SQL performance background, including execution plans, indexing, partitioning, query optimization, and materialization strategies.
- Experience designing multi-tenant systems where row-level security, data entitlement, and customer-specific access rules are critical.
- Strong understanding of data governance, data quality, lineage, naming standards, metric consistency, and documentation.
- Experience designing reporting or analytics solutions that work with large, complex, production datasets.
- Ability to translate complex business requirements into clean, scalable, and maintainable data architecture.
- Comfortable working closely with engineering teams using SQL Server and .NET/C# environments. Hands-on .NET/C# experience is helpful but not required.
- Strong collaboration skills, including the ability to work with product managers, developers, QA engineers, and business stakeholders.
- Excellent analytical, debugging, and problem-solving skills, along with strong written and verbal communication.
AI-Ready Data Foundation
While this is not an AI engineering role, we expect the data architecture to support future AI-assisted experiences. This means designing clean, trusted, well-documented, and secure data structures that can support natural language reporting, AI-assisted report creation, anomaly detection, intelligent payroll audits, and conversational analytics in the future.
The right candidate does not need to be an AI specialist, but should understand that AI is only as strong as the data foundation behind it.
Nice to Have
- Experience with healthcare, payroll, HCM, workforce management, or compliance-related data.
- Experience with SQL Server, Azure data services, data warehouses, lakehouses, dbt, Cube, Looker, Power BI, Metabase, or similar platforms.
- Experience designing semantic layers or data models that support natural language reporting or AI-assisted analytics.
- Experience with event-driven data models, data pipelines, or near-real-time reporting architectures.
- Experience working in a SaaS, multi-tenant software environment.
Why This Role Matters
Reporting and analytics is a major strategic investment for Empeon. This role will help define the data foundation that enables better reporting, better analytics, stronger decision-making, and future AI-driven capabilities for our clients.