We’re looking for a Data Architect who is equally at home across relational databases, open-source databases and cloud data warehouses. The company runs several data platforms side by side. You’ll keep them reliable, set the standards across them, and lead their convergence into one architecture, built on data extract and load methods that do not lock us into a single vendor. This is a hands‑on, AI‑first role: you will design and build inside our data engineering teams, handing much of the keyboard work to AI coding agents. You alone own the architecture and are accountable for every change to it, so nothing merges without your review.
This role reports to the VP of Data and partners closely with Engineering, Product, Clinical, and Security.
What You’ll Do:
- Design and own the end-to-end data architecture, including data models, storage, integration patterns, and data flows across our relational, document and cloud warehouse systems
- Define standards for data modeling, naming, quality, and documentation that engineering teams follow
- Work sprint by sprint inside our data engineering teams, directing AI coding agents such as Claude Code to write, test and document production SQL and pipelines, reviewing what they produce, and taking a share of production support
- Architect secure handling of protected health information (PHI) in line with HIPAA, HITRUST and SOC 2 requirements
- Design integrations with health plan and payer partners, including eligibility, claims, and clinical data feeds
- Build the data foundation for AI and analytics use cases, making sure data is accurate, accessible, and well governed
- Design data extract and load methods that avoid vendor lock-in, and lead the convergence of our data platforms, balancing performance, cost, and long‑term scalability
- Lead data governance practices, including lineage, access controls, and retention policies
- Translate business and clinical needs into technical data requirements with stakeholders across the company
What You Bring:
- 7+ years of experience in data engineering, data architecture, or a related field, with at least three years in an architect‑level role
- Deep expertise in data modeling (relational, dimensional, and NoSQL), modern data warehouse design, and migrating workloads between platforms
- Deep, hands‑on production experience with SQL Server (T‑SQL, SSIS, performance tuning), PostgreSQL, and Google BigQuery, plus workflow orchestration and transformation tools such as Airflow and dbt
- Strong SQL skills and working knowledge of Python or another data‑focused language
- Experience designing systems that handle PHI or other regulated data, with a working understanding of HIPAA and HITRUST
- Familiarity with healthcare data standards such as HL7, FHIR, or X12 EDI (strongly preferred)
- You already work AI‑first: you hand much of your hands‑on‑keyboard work to AI coding agents such as Claude Code and review their output with impeccable rigor before anything merges: correctness, performance, security and fit with the architecture. Experience supporting AI or machine learning data needs is a plus
- Clear communicator who can explain architecture tradeoffs to technical and nontechnical audiences