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nVent

Electrical enclosures, thermal management, fastening components.

Director – Enterprise Data and AI Architecture

Data ManagementConfirmed live in the last 24 hours
Full-timeSt Louis Park, MN, USAHybrid

About the Job

Requirements

  • A master's degree or Ph.D. in Computer Science, Engineering, Mathematics, Statistics, or a 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.
  • A 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 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, with the ability to present architecture options and tradeoffs clearly to executive audiences and engineering teams.
  • Strong facilitation skills and comfort leading workshops, architecture reviews, and cross-functional working sessions.
  • Comfort with ambiguity and the ability to shape structure from complex, evolving business requirements and organizational constraints.
  • 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, keeping near-term delivery aligned with long-term strategic direction.
  • Set technical strategy and architectural principles for the modern data stack and AI, translating enterprise business strategy into supporting capabilities.
  • Lead architecture governance by defining standards, patterns, and decision authority across domains, platforms, and acquired entities.
  • Advise executive leadership on build-versus-buy choices, platform strategies, and technology investment decisions, including options, tradeoffs, and potential value.
  • Shape the data and AI operating model 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, designed to scale from MVP to enterprise value.
  • Architect master data management solutions for critical data domains, focusing on data quality, matching, survivorship, and golden record management.
  • Define and maintain architecture decision records and ensure designs meet 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.
  • Design data integration strategies, harmonization approaches, and migration plans for M&A integration projects to enable rapid time-to-value from acquisitions.
  • Manage concurrent initiatives with competing priorities while maintaining quality and architectural integrity under delivery pressure.
  • Design and implement data integration patterns across batch, near-real-time, and streaming workloads that connect ERPs, SaaS platforms, operational systems, and the enterprise data platform.
  • Establish ETL/ELT pipeline design standards using tools such as dbt, Matillion, Informatica, and Snowflake native capabilities, and define data modeling standards for analytical and operational workloads.
  • Define AI and machine learning architecture across data pipelines, feature management, model serving, and generative AI patterns such as retrieval-augmented generation, vector stores, and agentic workflows.
  • Embed controls from a recognized responsible and governed AI 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, distinguish durable value from vendor marketing, and incorporate relevant advances into the enterprise roadmap.
  • Build trusted relationships with executive stakeholders, business leaders, and technology partners, serving as a 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 identify data requirements and translate them into architectural approaches.
  • Lead and develop a technical team, set clear expectations, provide ongoing coaching, and support career growth within the data organization.
  • Drive technical hiring decisions and team capacity planning with leadership, helping 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 technical and professional standards across the data organization and partner with data leaders to build organization-wide capability.

Desired Qualifications

  • Experience in M&A data integration and major platform consolidations is strongly preferred.

About the Company

nVent

Electrical enclosures, thermal management, fastening components.

nVent provides electrical connection and protection solutions in three segments: Enclosures, Thermal Management, and Electrical & Fastening Solutions; Enclosures shield electronics with standard and customized cabinets and cooling for data centers, industrial automation, and energy (brands include HOFFMAN and SCHROFF). Thermal Management covers heat tracing, floor heating, and fire-rated wiring, with RAYCHEM known for self-regulating technology. Electrical & Fastening supplies components to fix, fasten, and ground electrical systems (brands include ERICO and CADDY). Serving engineers, energy firms, data centers, and manufacturers worldwide, nVent aims to deliver reliable, integrated electrical infrastructure solutions.

Company size
1,001-5,000
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1903

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