Data Architect

Job Summary

We are seeking a highly seasoned Data Architect (Individual Contributor) with 20+ years of hands‑on experience spanning enterprise data platforms, AI data architecture, data governance, and data quality. The ideal candidate is a self‑driven, collaborative, and deeply technical leader who thrives on partnering with business and technology stakeholders to design and deliver enterprise‑scale data and AI solutions.

Responsibilities

• Enterprise Data Strategy & Architecture
• Define the target-state Data and AI architecture aligned with business goals and technology strategy.
• Establish architectural standards, principles, and best practices across the data ecosystem.
• Develop and maintain a multi-year roadmap covering data platforms, integrations, governance, and AI enablement.
• Stakeholder Collaboration & Leadership
• Partner closely with business and technical stakeholders to understand needs, define requirements, and co-create data solutions that deliver measurable outcomes.
• Translate complex technical concepts into clear, executive-ready communication.
• Provide architectural leadership and thought partnership across cross-functional teams.
• Analytical and structured thinker—comfortable navigating ambiguity and solving complex data problems.
• Highly self-directed, organized, and capable of independently driving strategic and technical workstreams.

Data Governance & Quality

• Design and implement enterprise data governance frameworks, including data ownership, stewardship, policy development, and operating models.
• Define data quality processes, including profiling, validation, controls, and lineage.
• Collaborate with security, compliance, and legal teams to ensure adherence to regulatory standards and privacy requirements.
• Establish and enforce data localization controls, ensuring data residency, sovereignty, and regional storage/processing requirements are met across all relevant jurisdictions.

Innovation and Continuous Improvement

• Stay current with emerging technologies and trends across Data Cloud, AI, and ML, evaluating opportunities for adoption.
• Develop reusable architectural patterns, accelerators, and reference designs to streamline delivery.
• Continuously refine the data and AI architecture to support business growth, agility, and innovation.

Minimum Qualifications

• A bachelor's degree and 10 years of professional work experience (or equivalent experience) is required.

Additional Qualifications

• Experience standing up enterprise data platforms or AI/ML ecosystems.
• Industry certifications in cloud architecture or data engineering.
• Experience with responsible AI, data ethics, or regulatory compliance.