Job Description
Principal Data Architect - Data Modernization | Onsite, US | 15+ years
\n
\n
Job Description:
\n
We are seeking a Principal Data Architect to serve as the design authority across a portfolio of large-scale data platform modernization programs. This architect sets architecture standards, drives data modeling and solution strategy across cloud data platforms, and leads a central enablement function that converts delivery learnings into reusable accelerators and playbooks. This is a hands-on architecture leadership role for someone who has personally architected legacy-to-modern transformations at enterprise scale.
\n
\n
Key Responsibilities
\n
- Own architecture standards, data modeling direction, and solution strategies across Snowflake, Databricks, and legacy conversion workstreams.
\n
- Chair design reviews across parallel delivery teams; ensure consistent, high-quality architecture decisions and safe migration and cutover designs.
\n
- Define validation and reconciliation strategies for large-scale data migrations, including parallel-run frameworks and tolerance models.
\n
- Direct an enablement team building accelerators, reusable frameworks, and delivery playbooks; drive adoption and measure reuse across programs.
\n
- Advise client architecture leadership; support architecture sign-off, risk assessment, and change management for platform transitions.
\n
- Champion AI-enabled engineering practices (code conversion, test generation, AI-assisted development) across delivery teams.
\n
\n
Qualifications
\n
- 15+ years in data architecture and engineering, with enterprise-scale architecture leadership across cloud data platforms.
\n
- MarTech domain expertise is a must: identity resolution, customer data, audience segmentation, suppression, and campaign data flows.
\n
- Deep, hands-on experience architecting data platform modernization programs (legacy to modern cloud platforms), including AI-enabled and accelerator-driven delivery, migration planning, data validation and reconciliation strategies, parallel runs, and cutover execution.
\n
- Strong data modeling depth (dimensional, medallion/lakehouse) and modern transformation frameworks (dbt or equivalent).
\n
- Proven design authority across multiple concurrent teams; ability to both lead and execute.
\n
- Snowflake and/or Databricks architecture certifications preferred; accelerator or IP development leadership a plus.
\n