Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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Staples has filed one layoff notice in the last twelve months, covering 109 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings

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About the job

Sr Data & AI Architect II/Work Model: Onsite, Framingham, MA

Staples is business to business. You’re what binds us together.

Team Summary: The Enterprise Data & AI team partners across Data Engineering, Data Science & AI, Product, Digital, Marketing, Sales, Analytics, and other technology teams to build trusted, scalable data and AI capabilities. The team establishes reusable architecture patterns and technical guardrails that strengthen security, consistency, engineering quality, and responsible AI adoption across the organization.

Role Summary: Staples is seeking a senior-level Data & AI Architect to lead the architecture of modern data and AI capabilities supporting marketing, customer engagement, digital experiences, sales, and enterprise decision-making. The Sr Data & AI Architect II will define scalable architecture across cloud data platforms, data products, semantic models, real-time data, analytics, machine learning, generative AI, and intelligent applications. This role will enable capabilities such as conversational analytics, Databricks Genie, AI agents grounded in trusted enterprise data, intelligent decisioning, recommendations, and personalization. The ideal candidate combines deep enterprise data architecture expertise with practical experience applying data and AI within customer-facing domains.

What you’ll be doing: • Own the current-state, transition-state, and target-state data and AI architecture supporting marketing, customer engagement, digital, sales, and analytics use cases. • Architect modern data platforms and reusable data products using technologies such as Databricks, Snowflake, cloud services, APIs, event streaming, and semantic models. • Establish governed data and context architectures that allow analytics, AI models, and AI agents to securely access trusted enterprise data. • Enable intelligent experiences such as conversational analytics, Databricks Genie, AI agents, recommendations, propensity models, and next-best-action capabilities. • Design reusable customer, account, marketing, product, sales, and engagement data products that support analytics, AI, personalization, activation, and measurement. • Define scalable architecture patterns across batch, real-time, streaming, API, structured, semi-structured, and unstructured data. • Establish standards for semantic models, data contracts, metadata, lineage, observability, data quality, privacy, security, and access controls. • Partner with Data Engineering and Data Science teams to operationalize machine learning and generative AI through governed data products, model outputs, APIs, and reusable services. • Translate marketing and customer opportunities into architecture decisions, proofs of concept, implementation roadmaps, and technology recommendations. • Lead architecture reviews, technology evaluations, and design sessions while documenting key decisions, dependencies, risks, and trade-offs. • Provide technical direction across engineering teams and ensure solutions align with enterprise architecture, security, privacy, data governance, and responsible AI standards. • Mentor architects and engineers and promote common data, AI, integration, and engineering patterns across the organization.

What you bring to the table: • Strong enterprise architecture, analytical, and problem-solving capabilities. • Ability to connect business opportunities with practical data and AI solutions. • Strong technical leadership and mentoring skills. • Strategic thinking with the ability to translate architecture into executable roadmaps. • Excellent communication skills and the ability to partner with business, engineering, data, and executive stakeholders. • Ability to operate effectively in a complex, rapidly evolving technology environment.

What’s needed- Basic Qualifications: • Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related field, or equivalent experience. • 10+ years of experience designing enterprise data platforms, data products, integration architectures, analytical systems, or high-volume data solutions. • Deep experience with modern cloud data platforms such as Databricks, Snowflake, BigQuery, or equivalent, including lakehouse and data warehouse architectures. • Experience designing data architectures supporting analytics, machine learning, generative AI, and intelligent applications. • Demonstrated experience in marketing, customer, digital commerce, sales, or similar customer-facing data domains. • Strong experience designing batch, streaming, API, and event-driven data architectures. • Strong knowledge of relational, dimensional, event, document, and semantic data-modeling approaches. • Experience building reusable data products, curated data layers, and semantic models for analytical and operational consumption. • Familiarity with conversational analytics, AI agents, RAG, vector search, and enterprise AI grounding. • Experience operationalizing machine learning or AI capabilities such as recommendations, propensity, lead scoring, next-best action, or generative AI use cases. • Experience with enterprise data governance, metadata, lineage, observability, data quality, privacy, security, and access controls. • Fluency in SQL and working knowledge of Python, Java, Scala, or another language used for modern data and AI engineering. • Demonstrated ability to lead architecture across multiple teams and communicate complex recommendations to senior business and technology leaders.

What’s needed- Preferred Qualifications: • Master's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field. • Experience with Databricks Genie, Mosaic AI, MLflow, Unity Catalog, Delta Lake, or comparable data and AI technologies. • Experience with AI-agent architecture, RAG, enterprise context and grounding, vector databases, agent evaluation, and responsible AI. • Experience designing semantic models and governed business metrics for self-service and conversational analytics. • Familiarity with Salesforce, Marketo, Optimove, Adobe, Hightouch, or comparable customer engagement and activation technologies. • Experience with real-time customer data, decisioning, recommendation systems, experimentation, attribution, incrementality, or closed-loop measurement. • Experience integrating enterprise data and AI platforms with downstream marketing, digital, sales, and customer-engagement systems. • Relevant cloud, data, AI, architecture, or security certifications.

We Offer: • Inclusive culture with associate-led Business Resource Groups • 22 days of PTO and Holiday Schedule (7 observed paid holidays + 1 floating holiday) • Online and Retail Discounts, Company Match 401(k), Physical and Mental Health & Wellness programs, and more!

The salary range represents the expected compensation for this role at the time of posting. The specific base pay may be influenced by a variety of factors to include the candidate's experience, skill set, education, geography, business considerations, and internal equity. In addition to base pay, this role may be eligible for bonuses, or other forms of variable compensation. #LI-LH1

Staples is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, age, national origin, protected veteran status, disability, or any other basis protected by federal, state, or local law.