Senior Data Architect (Data Foundation & AI Data Readiness)

Phase2

4d • $132,000 - $155,000 • Remote

About The Position

The Senior Data Architect will help enterprise clients modernize their data ecosystems, improve data reliability and accessibility, and prepare data for analytics, AI-assisted experiences, workflows, and other uses. The role diagnoses complex data challenges and architects practical solutions that produce measurable business value.

The architect will design and help build scalable data solutions while establishing standards and patterns that make data easier to find, understand, use, and govern. Working with client data owners, engineering teams, and Phase2 colleagues, the role delivers prototypes and production-ready capabilities, demonstrates progress through measurable outcomes, and communicates results to executives. The architect will also help establish reusable data architecture, engineering, and AI-readiness frameworks for Phase2's emerging enterprise data capabilities.

The work spans client leadership, strategy and architecture, implementation and delivery, and quality and governance. It includes advising and pitching the capability to clients, making the business case for foundational data work, designing data platforms and pipelines, establishing semantic and context standards, and ensuring data quality, documentation, lineage, security, compliance, and responsible data use. The role works in a remote-first environment, with travel expected, sometimes frequently.

Requirements

• At least 8 years of experience in data engineering, data architecture, or a closely related discipline such as analytics engineering, data platform engineering, or MDM architecture.
• Demonstrated ability to establish and apply data quality, testing, and validation practices that ensure data accuracy and reliability.
• Ability to prototype and build solutions across the data and application stack to accelerate learning and delivery.
• Demonstrated experience architecting and delivering production data platforms and solutions, including data integration, transformation, modeling, and storage, with sound judgment around scalability, performance, reliability, and cost.
• Fluency in SQL and data modeling, with sound judgment about modeling approaches such as Kimball and Data Vault and when to apply them.
• Ability to trace client complaints, such as incorrect reports, unreliable AI answers, or stalled migrations, to their underlying data root causes.
• Experience navigating complex stakeholder environments and balancing technical, business, security, and compliance considerations to build alignment.
• Strong executive communication and storytelling skills, including reporting progress against defined scorecards or KPIs and influencing roadmaps.
• Comfort delivering visible progress in short cycles, providing clients tangible movement every week or two.
• Generalist orientation and comfort with ambiguity, including the ability to handle varied data migration and large-scale pipeline work.

Nice To Haves

• Experience supporting regulatory audits or compliance reviews in regulated industries such as financial services or healthcare.
• Experience bridging data product management and AI solution delivery.
• Experience in metadata management and data catalog ecosystems, including improving discoverability and interpretability.
• Full-stack engineering experience supporting rapid prototyping and experimentation.
• Experience building or governing controls and metrics layers for enterprise analytics at scale.
• Experience directing AI agents or agentic tooling as a delivery mechanism.

Responsibilities

• Help pitch and sell the data capability alongside sales and account teams.
• Lead technical client conversations, diagnose underlying data challenges, and translate business needs into practical solutions.
• Make the business case for foundational data work by quantifying benefits such as cost avoidance, reporting-time savings, and reduced duplicate work.
• Define measurable outcomes and progress indicators, and communicate results through regular demos and executive updates.
• Collaborate with senior technical leaders to establish reusable architectures, technical standards, and delivery approaches for enterprise data capabilities.
• Partner with Marketing Technology Strategists and the Data & Insights team to align semantic standards and warehouse architecture with marketing data work such as CDP, attribution, and activation.
• Establish semantic and context-layer standards and resolve gaps that affect data consistency, accessibility, and reliability.
• Work with client data owners to establish trusted, reusable data foundations across systems, teams, and AI applications.
• Design and deliver metadata, lineage, and data quality practices that improve discoverability and reduce ambiguity in AI-driven analysis.
• Define scalable data access and integration patterns for analytics, AI applications, copilots, and agents.
• Architect, build, and optimize data platforms and pipelines for ingestion, integration, transformation, modeling, and storage, considering scalability, performance, reliability, and cost.
• Design and deliver proofs of concept and production-ready data solutions across diverse client environments.
• Collaborate with software engineers and technical specialists to implement solutions, establish reusable engineering patterns, and use AI-assisted development tools where appropriate.
• Establish data quality, validation, and testing practices that ensure solutions are accurate, reliable, and fit for purpose, including applicable AI use cases.
• Define technical standards and review data solutions developed by engineers and AI-assisted tooling for consistency, maintainability, and correctness.
• Incorporate documentation, metadata, lineage, and governance practices to support security, compliance, auditability, and responsible data use.

Benefits

• Competitive compensation package considering various factors.
• Medical, dental, vision, life insurance, disability coverage, and supplemental insurance.
• Wellness program with rewards for participation.
• 401(k) with a 3% employer contribution, no match required, and 100% vesting after 90 days.
• 16 paid vacation days, 4 personal days, and 1 volunteer day each year; vacation and personal time increase with tenure.
• Up to 12 weeks of fully paid leave for birthing parents and up to 6 weeks of fully paid bonding leave, based on tenure.
• Adoption and foster placement support, with the option to extend leave through additional unpaid time off.
• $500 stipend to personalize and equip a home workspace.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed