Principal Data Platform Engineer

Duluth Trading Company is hiring a Principal Data Platform Engineer to own the architecture, reliability, and evolution of its enterprise data platform and master data management systems. The role leads data engineering, platform and AI enablement, governance, and roadmap delivery in partnership with technical and business stakeholders.

Responsibilities:

• Own the architecture and operations of the enterprise data platform: ingestion (Fivetran, Airbyte), transformation (dbt), warehousing (BigQuery), and BI/serving layers (Looker, Hex)
• Manage cloud infrastructure as code using Terraform; ensure repeatable, version-controlled platform deployments
• Implement and maintain monitoring, observability, and data quality frameworks across the platform
• Own the Pimcore MDM platform end-to-end as the canonical source for item and location master data
• Define master data architecture standards and govern the item and location data domains
• Ensure master data flows correctly between operational systems and the analytical platform
• Define and evolve the data architecture roadmap in partnership with engineering leadership
• Architect the integration between operational master data (Pimcore) and the analytical platform (BigQuery)
• Set technical standards for data modeling, pipeline design, and platform integration
• Evaluate and introduce new technologies that improve platform capability or reduce cost
• Own the data platform roadmap, including prioritization, sequencing, and alignment with business needs across Customer, Marketing, Merchandising, Product Development, Inventory Control, and Supply Chain
• Translate business requirements into platform and analytics deliverables; define success measures and acceptance criteria
• Manage the data team's intake and delivery pipeline against business priorities
• Communicate roadmap, trade-offs, and delivery status to executive stakeholders
• Provide technical leadership for a team of data engineers and Looker developers
• Set technical direction and priorities for the data team's work
• Review architecture, code, and design decisions across team deliverables
• Mentor and grow team members on data platform engineering, data modeling, and BI development practices
• Drive cost optimization across the data platform through architecture decisions, vendor consolidation, and infrastructure efficiency
• Establish operational practices that improve reliability and reduce manual intervention
• Build and maintain AI-ready data: ensure data quality, consistency, and structure across the platform so AI tools and agents can run on trustworthy data
• Drive adoption of AI capabilities across the platform (Looker agents, Hex AI) and integrate emerging AI tools into data team workflows
• Establish data governance standards across the platform, including data quality, lineage, master data stewardship, and access controls
• Define standards and guardrails for AI usage within the data platform, and identify high-value AI use cases for business stakeholders

Requirements:

• Bachelor's Degree
• 15+ years of IT experience, including extensive data engineering and platform work, with 5+ years at a senior or lead level
• Expert-level SQL, Python for data engineering, and data modeling fundamentals (dimensional, SCD, fact/dimension design)
• Deep expertise across the modern data stack: GCP, BigQuery, dbt, Fivetran, Airbyte, Looker, Hex, and orchestration tools (Dagster, Airflow)
• Strong infrastructure-as-code background, particularly Terraform on GCP
• Hands-on experience integrating AI capabilities into analytics platforms (Looker agents, Hex AI)
• Experience owning master data platforms (Pimcore or equivalent)
• Demonstrated technical leadership of engineering teams and ownership of platform roadmaps
• Track record of platform-level decisions with measurable business impact and executive stakeholder partnership
• Authorization to work in the United States without sponsorship