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Principal Data Architect - Data Modernization (MarTech)

Posted 2 days ago

anblicksDallas (TX)

SENIORITY

Manager

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About the role

Job Description: Principal Data Architect - Data Modernization (MarTech) | Onsite, US | 15+ years Anblicks is 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.
Key Responsibilities: Own architecture standards, data modeling direction, and solution strategies across Snowflake, Databricks, and legacy conversion workstreams. Chair design reviews across parallel delivery teams; ensure consistent, high-quality architecture decisions and safe migration and cutover designs. Define validation and reconciliation strategies for large-scale data migrations, including parallel‐run frameworks and tolerance models. Direct an enablement team building accelerators, reusable frameworks, and delivery playbooks; drive adoption and measure reuse across programs. Advise client architecture leadership; support architecture sign‐off, risk assessment, and change management for platform transitions. Champion AI‐enabled engineering practices (code conversion, test generation, AI‐assisted development) across delivery teams.
Qualifications: 15+ years in data architecture and engineering, with enterprise‐scale architecture leadership across cloud data platforms. MarTech domain expertise is a must: identity resolution, customer data, audience segmentation, suppression, and campaign data flows. 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. Strong data modeling depth (dimensional, medallion/lakehouse) and modern transformation frameworks (dbt or equivalent).Proven design authority across multiple concurrent teams; ability to both lead and execute. Snowflake and/or Databricks architecture certifications preferred; accelerator or IP development leadership a plus.

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