Principal Data Architect

CVS Health•Work At Home-Colorado, CO

6d•$144,200 - $288,400•Remote

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Principal Data Architect is the senior individual contributor accountable for data architecture across Aetna Technology. This role sets the technical direction for how data is modeled, stored, moved, governed, and consumed across a multivendor data estate spanning multiple clouds. The Principal Data Architect defines the data reference architectures and strategy that domain teams build on, establishes where the singular systems of record live, and serves as Aetna Technology's deepest technical authority on data — driving outcomes through design authority and influence rather than direct reports. This role can work remotely from anywhere in the continental USA.

Requirements

12+ years in technology, with deep, hands-on data architecture experience at Aetna Technology scale.
Expert-level data platform architecture across multivendor, multicloud environments (e.g., Snowflake, GCP/BigQuery, AWS); fluent across modeling, pipelines, and consumption layers.
Demonstrated ownership of enterprise data architectures and golden-path patterns for data products.
Strong command of data governance, lineage, quality, and regulated-data controls (PHI or equivalent).
Working knowledge of data mesh, domain ownership, and systems-of-record design.
Track record of driving technical outcomes through influence and design authority as an individual contributor.
Bachelor's degree in Computer Science, Engineering, or a related field or equivalent experience.

Nice To Haves

Experience in healthcare, health insurance, or similarly regulated industries.
Hands-on background with the data infrastructure behind AI/ML — feature stores, retrieval, and data contracts for model and agent workloads.
Familiarity with FinOps and cost-aware data architecture, able to tie design decisions to dollar impact.
Experience with infrastructure-as-code and automated policy/guardrail enforcement.

Responsibilities

Own the Aetna Technology data reference architectures — ingestion, storage, transformation, semantic, and consumption layers — across a multivendor, multicloud data estate.
Define the data mesh operating model: domain-owned data products with clear contracts, and the platform capabilities that make domain ownership viable rather than fragmenting.
Carve out and protect the singular systems of record — establishing which domain owns which authoritative dataset and how others consume it.
Design and maintain the golden paths for pipelines and data products — patterns for ingestion, modeling, and publishing that let teams ship without re-solving solved problems.
Embed data governance, lineage, and quality as automated gates in the pipeline, not as a downstream review.
Define controls for regulated and sensitive data (including PHI) — classification, access, masking, and retention inherited by default across the portfolio.
Establish zero-trust patterns for data access — identity, least privilege, and blast-radius reduction for authoritative datasets.
Provide the data architecture underpinning Aetna Technology AI capabilities — feature readiness, retrieval, and the data contracts that AI and agentic systems depend on.
Establish the semantic and metrics layer that lets analytics and dashboards scale reliably to people-managers and business users across Aetna.
Partner with AI and analytics platform teams on the data infrastructure required to serve workloads securely and cost-effectively at scale.
Author the data standards enforced as automated gates and golden-path defaults, not as a review queue.
Contribute to architecture governance — reference architectures, technology radar input, and design reviews — in partnership with Enterprise Architecture.
Evaluate emerging data platform and tooling options and make directional recommendations on adoption.
Translate data architecture trade-offs into clear, decision-oriented narratives for senior technology leaders and peer architects.
Coach and raise the bar for Solution Architects and senior engineers through design reviews and system-level reasoning — without direct reporting relationships.
Act as a credible technical partner to strategic data platform vendors and internal platform teams.