Principal Data Architect

Blue Cross of Idaho is seeking a Principal Data Architect to join our Data Strategy & Engineering team's Cloud Enterprise Data Platform (EDP) journey. As we modernize and optimize our Data & Analytics program through legacy data platforms consolidation onto AWS & Snowflake redesign, we will be enabling a suite of leading capabilities to support the spectrum of business needs with key cloud and big data technologies to include: AI/ML, streaming data, data lake and data warehouse, as well as self-service and delivered reporting.

This important role will help lead our EDP architecture, roadmap, and integration strategy, as well as play a key role in the build of these capabilities.

Strong preference for flexible hybrid location (onsite Meridian Idaho campus + local work-from-home); there may be opportunity for fully remote work within a mutually acceptable location.

• Define multi-tenant enterprise data architecture for the platforms
• Lead data architecture practice and represent Data Engineering at the enterprise level
• Technical subject matter expert in the data ecosystem, including AWS/Snowflake, providing input into architecture, platforms, and development strategies and methodologies – includes mentorship of engineering and platform teams via design reviews, code reviews, etc.
• Define data engineering and data platform integration framework and standards. Mentor, coach and build learning program to efficiently and quickly onboard new people in the team and ensure standards are understood and followed.
• Facilitate cross-team collaboration for defining and building enterprise data management architecture from principles to tools, oversee cross‑functional adoption of the new architecture, and enable a new level of engineering efficiency when working with data.
• Direct the strategy and implementation for migration from the existing data warehouse platforms onto the new Enterprise Data Platform (EDP) on AWS/Snowflake.
• Lead technical direction of the team, driving the necessary changes and recommending appropriate technology choices working collaboratively with Architecture, Platform, Dev Ops, Security, and Project teams; influence technical direction with expert input into project decisions.
• Lead the shift towards Dev Sec Ops  processes for the Data & Analytics delivery functions, emphasizing continuous integration, release management, and automated testing to maximize development agility and improve time to market.
• As the data platform product manager, drive the data platform technical roadmap to prioritize and build new features that serve the business teams and standardize templates for technical work
• Interface with key business functions (i.e., Compliance, Actuarial, Marketing, Operations, Clinical, etc.) and IT Analysis teams to assess business functional requirements and translate them into data and integration requirements.
• Guide onsite/onshore/offshore technical resources from consulting partners, communicate architecture standards and best practices, establish a high impact development process, drive excellence in all deliverables.
• Establish daily cadence with project team to prioritize and execute work items through adoption of Agile principles and processes.
• Manage relationships with external vendors to determine technical competence and identify integration opportunities.
• Be a hands‑on practitioner for end‑to‑end delivery of AWS/Snowflake platforms, capabilities, and content

• Ability to understand, drive, and deliver technology solutions in AWS and Snowflake.
• Demonstrated understanding of Data architecture and components, especially for Data Warehousing, including Snowflake, dbt Data transformations, Airflow, Data Cataloging tools like Alation; other key integration platforms like Boomi/Fivetran, BI tools like Tableau/Power BI/Sigma, and AI/ML tools like Dataiku/Cortex/Snowflake Intelligence.
• Demonstrated understanding of and experience with modern Data Warehouse concepts, including Data Lake/Data Warehouse/Data Mart implementations, SQL-based transformations, and ELT methodology.
• Understanding of Data Mesh principles, treating data as product, emphasizing domain…