Data and AI Architect Manager

Avanade•Seattle, WA

About The Position

The Data and AI Architect Manager is a leadership role responsible for shaping and scaling enterprise data, analytics, and AI solutions that advance business strategy and deliver measurable client outcomes. As a trusted advisor and subject matter expert, the role helps clients modernize complex data estates and accelerate digital transformation across the Microsoft ecosystem, with a focus on AI-native data platform solutions. The role leads end-to-end architecture and solution design, connecting business priorities, operating models, data and AI platforms, and application landscapes. It provides hands-on technical oversight from architecture through implementation, guides critical decisions with delivery teams, and partners with senior client leaders to navigate complexity and ensure secure, scalable, high-performing solutions deliver lasting business impact.

Requirements

At least 7 years of experience in data engineering, knowledge engineering, data architecture, analytics, AI, or consulting roles, including at least 2 years in a client-facing leadership capacity.
At least 2 years leading enterprise-scale Data & AI platform modernization initiatives, including platform transformations, analytics modernization, or AI-enabled data platform programs.
Demonstrated experience supporting or leading deals valued at $2 million or more, or equivalent enterprise-scale opportunities.
At least 5 years of hands-on experience designing and implementing enterprise data platforms using Microsoft Azure Data Services, Databricks, Snowflake, Microsoft Fabric, or comparable technologies.
At least 2 years of experience architecting cloud-based data solutions, such as data lakes, lakehouses, cloud analytics platforms, or modern data warehouses.
At least 5 years of experience using Python and SQL for data engineering, analytics, integration, and platform development.
At least 3 years of experience delivering large-scale data migration, integration, governance, or modernization programs.
At least 2 years leading client workshops, executive stakeholder engagements, architecture reviews, and technical strategy discussions.
At least 3 years of experience with DevOps, DataOps, MLOps, SDLC, and Agile delivery methodologies.
At least 2 years applying generative AI, machine learning, advanced analytics, or agentic AI solutions in enterprise environments.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or a related quantitative field, or equivalent experience. The posting specifies a minimum of 10 years of experience without a degree or 8 years with an associate degree.
Ability to work a flexible schedule as business needs require, with reasonable accommodation where required by law.
Ability to travel domestically and internationally as business needs require.
Deep expertise in the Microsoft Data & AI platform and ecosystem.
Expertise in knowledge engineering, knowledge graph development, data modeling, semantic modeling, and ontologies.
Technical skills in Microsoft Fabric, Databricks (Data Platform and Genie), Python, Neo4J, SQL, Power BI, Foundry, and Copilot Studio.
Strong delivery acumen, including translating complex requirements into clear priorities, decisive action, and measurable client outcomes.
Ability to lead multidisciplinary teams through complex delivery challenges while maintaining momentum, quality, and accountability.
Exceptional communication and interpersonal skills, including the ability to build trusted relationships with senior client stakeholders.
Ability to drive consensus and architectural decision-making across business and technology stakeholders.
Ability to operate strategically and tactically, balancing executive vision with hands-on technical leadership.
Strong organization, analytical and problem-solving skills, and strategic thinking capabilities.
Commitment to innovation, continuous learning, high-quality client outcomes, and helping clients realize business value through modern data platforms and AI-driven transformation.

Nice To Haves

Microsoft Certified Azure Solutions Architect Expert, Azure Data Engineer Professional, Fabric Analytics Engineer, AI Engineer, or equivalent certification.
Experience in management consulting and/or systems integration environments.
Advanced degree in Computer Science, Engineering, Data Science, Applied Mathematics, Statistics, Machine Learning, or a related quantitative discipline.
Strong experience with Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Foundry, Copilot Studio, and Snowflake.
Experience designing and implementing Lakehouse, Data Mesh, Cloud Scale Analytics, Modern Data Warehouse, or Fabric-based architectures.
Ability to architect integrations between AI agents and enterprise applications, APIs, MCP servers, data platforms, Microsoft 365 services, and business processes.
Knowledge of streaming analytics, real-time intelligence, IoT, Digital Twins, and event-driven architectures.
Experience developing enterprise data and AI governance, data quality, metadata management, master data management strategies, and responsible AI.
Ability to articulate Data & AI use cases across industries including Manufacturing, Health & Life Sciences, Retail, Financial Services, and Resources.
Strong stakeholder management skills and experience influencing senior technology and business leaders.
Experience presenting architectural designs and investment strategies to senior client stakeholders.

Responsibilities

Lead enterprise data, analytics, and AI architecture, aligning technical decisions with client strategy, delivery priorities, and industry practices.
Translate complex business needs into platform architectures, modernization roadmaps, analytics capabilities, and AI-enabled solutions.
Architect and oversee secure, scalable enterprise data platforms using Microsoft Fabric, Azure Data Services, Databricks, Snowflake, SQL, Python, Foundry, and cloud-native technologies.
Lead client workshops, architecture reviews, and stakeholder forums to align technical direction, accelerate decisions, and remove delivery roadblocks.
Create and champion reusable assets, accelerators, and delivery methods that improve engagement quality, speed, and consistency.
Establish architecture governance, quality standards, and technical guardrails for data migration, analytics modernization, reporting, and AI programs.
Shape delivery plans through estimation, technical design, architecture governance, and implementation roadmaps.
Partner with senior client leaders and account teams to connect data and AI investments to measurable business outcomes and long-term value.
Provide hands-on technical oversight from architecture through implementation, validating design choices and ensuring enterprise-scale performance.
Anticipate and resolve technical risks, dependencies, and delivery challenges before they affect scope, quality, or outcomes.
Guide and mentor architects, engineers, and cross-functional delivery teams, raising technical standards and supporting confident execution.
Coordinate with global teams and technology partners to bring appropriate expertise to engagements, share knowledge, and scale Data & AI capabilities.
Apply emerging advances in data engineering, generative AI, agentic AI, real-time intelligence, IoT, and cloud platforms to improve client solutions.