Director, Enterprise Data and AI Architecture

nVentSaint Louis Park, MN
$172,900 - $257,000Hybrid

About The Position

As Director of Enterprise Data and AI Architecture at nVent, you will define the technical direction for how data and AI create value across the organization. You will shape our multi-year architecture strategy, enable enterprise reference architectures, and partner with executives to align technology investment with business priorities, while staying engaged in the technology to make sound, hands-on design decisions. This role demands architectural vision, deep technical expertise across the modern data, analytics, and AI stack, and the business acumen to translate complex data challenges into solutions that deliver lasting value. You are a change agent with an enterprise architecture focus who will engage leadership stakeholders on our highest priority initiatives and business transformation programs. You will define the blueprint for how governed data flows to power decision-making and AI solutions across the organization, and you will set the architecture standards, principles, and governance that keep that blueprint coherent as our company scales and grows.

Requirements

  • Master's degree or Ph.D. in Computer Science, Engineering, Mathematics, Statistics, or related technical field.
  • 12+ years of experience across data engineering, data architecture, analytics, and enterprise or solution architecture roles
  • 5+ years in an enterprise or solution architecture leadership role with demonstrated ownership of enterprise-scale data, analytics, and AI solutions
  • Proven track record of delivering production-grade solutions across the modern data stack
  • Demonstrated experience setting technical strategy and multi-year architecture roadmaps, and influencing executive technology investment decisions
  • Hands-on experience architecting AI and machine learning solutions, including modern generative AI patterns, in production environments
  • Experience in M&A data integration and major platform consolidations is strongly preferred
  • Experience working with executive stakeholders and leading cross-functional programs in a matrixed organization
  • Demonstrated experience directly managing technical professionals, including hiring, coaching, performance management, and career development of data engineers, architects, or related roles
  • Executive presence and communication skills: able to present architecture options and tradeoffs to executive audiences with equal clarity as to an engineering team
  • Strong facilitation skills, comfortable leading workshops, architecture reviews, and cross-functional working sessions
  • Comfortable with ambiguity; able to shape structure from complex, evolving business requirements and organizational constraints
  • Collaborative, curious, and committed to continuous learning in a fast-moving data and AI landscape

Nice To Haves

  • Relevant certifications, such as Snowflake SnowPro Core/Advanced, AWS Solutions Architect, or CDMP/TOGAF are a plus

Responsibilities

  • Own the enterprise data and AI reference architecture and the multi-year technology roadmap to deliver it, keeping near-term delivery aligned with long-term strategic direction
  • Set the technical strategy and architectural principles for the modern data stack and AI, translating enterprise business strategy into the capabilities required to support it
  • Lead architecture governance, defining the standards, patterns, and decision authority that keep solutions coherent across domains, platforms, and acquired entities
  • Advise executive leadership on build versus buy, platform strategies, and technology investment decisions, framing the options, tradeoffs, and the nature of the value each path can unlock
  • Shape the data and AI operating model in partnership with leadership, defining how architecture, engineering, governance, and data capabilities deliver enterprise outcomes
  • Lead end-to-end architecture design for enterprise data solutions spanning ingestion, integration, storage, modeling, and consumption layers, designed to scale from MVP to enterprise value
  • Architect master data management (MDM) solutions covering critical data domains with a focus on data quality, matching, survivorship, and golden record management
  • Define and maintain architecture decision records and ensure designs adhere to enterprise standards for security, regulatory compliance, and performance, embedding data governance from the start
  • Own vendor relationships and technical roadmaps across the data platform ecosystem, partnering to evaluate emerging capabilities and plan platform investments
  • Lead complex data projects from discovery through production delivery, managing scope, dependencies, risks, and timelines
  • Engage in M&A integration projects, designing data integration strategies, harmonization approaches, and migration plans that enable rapid time-to-value from acquisitions
  • Manage multiple concurrent initiatives with competing priorities, maintaining quality and architectural integrity under delivery pressure
  • Design and implement data integration patterns across batch, near-real-time, and streaming workloads connecting ERPs, SaaS platforms, operational systems, and the enterprise data platform
  • Establish standards for ETL/ELT pipeline design using tools such as dbt, Matillion, Informatica, and Snowflake native capabilities, and define data modeling standards for analytical and operational workloads
  • Define our architecture for AI and machine learning, spanning data pipelines, feature management, model serving, and the patterns for generative AI such as retrieval-augmented generation, vector stores, and agentic workflows
  • Ensure adherence to standards for responsible and governed AI by design, embedding the controls of a recognized framework such as the NIST AI Risk Management Framework into solution architecture from the start
  • Architect the analytics and semantic layer that delivers trusted, consistent metrics to business intelligence, self-service analytics, and AI consumers across the enterprise
  • Partner with AI governance, security, privacy, and legal stakeholders to ensure AI solutions are scalable, compliant, and production grade
  • Evaluate emerging AI and data capabilities, separating durable value from vendor marketing, and fold the relevant advances into the enterprise roadmap
  • Build trusted relationships with executive stakeholders, business leaders, and technology partners, serving as a credible bridge between business needs and technical solutions
  • Lead workshops and architecture reviews with cross-functional teams including Finance, Supply Chain, Sales, HR, and IT to uncover data requirements and translate them into actionable architectural approaches
  • Lead and develop a technical team, setting clear expectations, providing ongoing coaching, and supporting career growth within the data organization
  • Drive technical hiring decisions and team capacity planning in partnership with leadership, helping to shape the skills and structure needed to support a growing organization
  • Foster a high-performance team culture grounded in accountability, collaboration, and continuous learning; model the technical and professional standards across the data organization, and partner with data leaders to build organization-wide capability

Benefits

  • Medical, dental, and vision plans along with flexible spending accounts, short-term and long-term disability benefits, critical illness, accident insurance and life insurance.
  • A 401(k) retirement plan and an employee stock purchase plan — both include a company match.
  • Tuition reimbursement, caregiver, personal and parental leave, back-up care services, paid time off including volunteer time, a well-being program, and/or legal & identity theft protection.
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