Principal Data Engineer

Principal Data Platform Engineer

Role Summary

The Principal Data Platform Engineer owns the architecture, reliability, and evolution of the enterprise data platform spanning both the analytical data stack and master data management. This is a senior role responsible for the systems and infrastructure that enable analytics, reporting, AI and operational data integrity across the company.

Key Responsibilities

Platform Engineering & Infrastructure

• Own the architecture and operations of the enterprise data platform: ingestion (Fivetran, Airbyte), transformation (dbt), warehousing (BigQuery), and BI/serving layers (Looker, Hex, python)
• 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

Master Data & Domain Architecture

• 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

Architecture & Technical Leadership

• 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

Platform Roadmap & Stakeholder Partnership

• 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

Team Leadership

• 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

Cost & Operational Excellence

• 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

AI Enablement & Data Governance

• 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

Required Experience & Skills

• 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

Scope & Impact

• Senior Leader managing the data engineering team directly and reporting into the Senior Director of e-commerce, Application Architecture and Data Platformsfter
• Technical authority across data engineering, analytics, BI, and master data functions
• Direct partnership with director-level stakeholders on data strategy and architecture