You will collaborate closely with engineering, security, compliance, and business leaders to translate validated architectural strategies into enterprise-wide patterns, data contracts, governance models, and technology roadmaps that enable trusted, secure, and responsible use of data and AI at scale.
Primary Responsibilities: - Define and evolve the target-state data architecture vision - how data is modeled, stored, governed, and served across the enterprise - with a clear path from current state to future state
- Stay grounded in reality: personally build and run hands-on pilots and proof-of-concept implementations that validate architectural recommendations before asking the organization to adopt them
- Design semantic and metadata layers, ontologies, and knowledge systems that let humans and AI agents reason over the same enterprise data, proven out through your own working prototypes
- Evaluate emerging AI research, technologies, and architecture trends - including RAG, agentic patterns, and vector/embedding systems - to inform solution design and strategic investment decisions
- Author reference architectures, design patterns, and data contracts that dozens of engineering teams can adopt and build against, grounded in what your pilots have proven works
- Establish data governance, data quality, privacy, security, and AI safety frameworks that protect business assets while accelerating delivery for the teams building on top of them
- Drive strategic architectural alignment across large engineering organizations through technical influence, documentation, and validated proof points rather than delivery authority
- Partner closely with engineering, security, legal, compliance, and infrastructure leaders to evaluate, build, buy, or retire core data technologies and shape multi-year platform investments
- Leverage enterprise-approved AI tools and automation platforms to accelerate your own pilot work and to model responsible, efficient adoption of AI for the teams that follow your patterns
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications: - 15+ years of experience in data architecture, data engineering, data analytics, information management, or closely related technical disciplines
- 10+ years of experience defining, evaluating, and validating enterprise-scale data architecture strategies through proofs of concept, pilots, architecture reviews, and production adoption
- 7+ years of experience in senior architecture, enterprise architecture, or technical leadership roles with responsibility for setting technology strategy and influencing enterprise-wide architectural direction
- 5+ years of hands-on experience designing and validating data models across multiple paradigms, including dimensional modeling, Data Vault, semantic layers, knowledge graphs, and vector/embedding representations
- 5+ years of experience with modern cloud data platforms and distributed data architectures, including Snowflake, Databricks, BigQuery, Azure Synapse, or equivalent technologies, as well as lakehouse and streaming architectures
- 3+ years of hands-on experience designing, prototyping, or piloting Generative AI and LLM-powered solutions, including retrieval-augmented generation (RAG), grounding strategies, evaluation frameworks, vector search, and agentic architectures
- 3+ years of Python and SQL experience, with the demonstrated ability to independently build prototypes, proofs of concept, and architecture validation implementations
- Hands-on experience designing and evaluating enterprise metadata, data governance, data catalog, lineage, semantic, and AI-ready data platform capabilities
- Proven experience establishing enterprise data architecture standards, reference architectures, data contracts, and governance models across large, distributed engineering organizations
- Demonstrated ability to drive architectural transformation and technology adoption through technical leadership, executive communication, influence, and validated proof points rather than direct organizational authority
- Experience working in highly regulated environments with solid security, privacy, compliance, and risk management requirements
- Ability to work onsite in Minneapolis, MN
Preferred Qualifications: - Master's degree or advanced training in Computer Science, Data Science, or a related discipline
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent professional experience)
- Experience leading a data architecture function at a high-growth product company or AI-native organization
- Background in machine learning engineering, applied AI research, or production ML systems
- Published technical writing, conference speaking engagements, or open-source software contributions in data architecture or AI
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 - $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
