Sr Data & AI Architect II

Staples Inc. • Framingham, MA

9h • $142,100 - $192,900 • Onsite

About The Position

Staples is seeking a senior-level Data & AI Architect to lead architecture for modern data and AI capabilities supporting marketing, customer engagement, digital experiences, sales, and enterprise decision-making. The role defines scalable architecture across cloud data platforms, data products, semantic models, real-time data, analytics, machine learning, generative AI, and intelligent applications. These capabilities include conversational analytics, Databricks Genie, AI agents grounded in trusted enterprise data, intelligent decisioning, recommendations, and personalization. The position calls for deep enterprise data architecture expertise and practical experience applying data and AI in customer-facing domains.

The Enterprise Data & AI team works across Data Engineering, Data Science & AI, Product, Digital, Marketing, Sales, Analytics, and other technology teams to build trusted, scalable data and AI capabilities. It establishes reusable architecture patterns and technical guardrails that support security, consistency, engineering quality, and responsible AI adoption.

The architect owns current-, transition-, and target-state architecture; defines and promotes reusable data products and architecture patterns; establishes governance and context architectures; and partners with engineering and data science teams to operationalize machine learning and generative AI. The role also leads architecture reviews and technology evaluations, guides implementation roadmaps, and mentors architects and engineers. This position is onsite in Framingham, Massachusetts.

Requirements

• 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 that support 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.
• 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 and ability to translate architecture into executable roadmaps.
• Excellent communication skills and ability to partner with business, engineering, data, and executive stakeholders.
• Ability to operate effectively in a complex, rapidly evolving technology environment.

Nice To Haves

• 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.

Responsibilities

• Own 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 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 for 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; document decisions, dependencies, risks, and trade-offs.
• Provide technical direction across engineering teams and ensure alignment 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.

Benefits

• Inclusive culture with associate-led Business Resource Groups.
• 22 days of PTO and a holiday schedule with 7 observed paid holidays and 1 floating holiday.
• Online and retail discounts.
• Company Match 401(k).
• Physical and mental health and wellness programs.
• The role may be eligible for bonuses or other forms of variable compensation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior