Principal Data Platform Engineer

Principal Data Platform Engineer Remote role Compensation: $80 - $85 ABOUT THE ROLE

Our Client is seeking a Principal Data Platform Engineer to lead the architecture, reliability, and evolution of their enterprise data platform, spanning both analytical data stacks and master data management. As a senior leader reporting to the Senior Director of e-commerce, Application Architecture, and Data Platforms, you will be responsible for the systems and infrastructure that enable analytics, reporting, AI, and operational data integrity across the company. This role is pivotal in defining technical standards, driving the data platform roadmap in alignment with business needs, and providing technical leadership to a team of data engineers and BI developers. You will partner directly with executive stakeholders, manage the end-to-end data platform architecture, implement cloud infrastructure as code, ensure data quality and observability, and own the master data management platform. Your work will have significant impact on the company’s data strategy, operational excellence, and ability to leverage AI for business value. WHAT YOU'LL DO

Own the architecture and operations of the enterprise data platform, including data ingestion (Fivetran, Airbyte), transformation (dbt), warehousing (BigQuery), and BI/serving layers (Looker, Hex, Python) Manage cloud infrastructure as code using Terraform to ensure repeatable, version-controlled platform deployments Implement and maintain monitoring, observability, and data quality frameworks across the platform Own and govern the master data management (MDM) platform (Pimcore or equivalent), defining architecture standards and ensuring data flows between operational and analytical systems Define master data architecture standards and govern 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 to 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, defining 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, direction, and mentorship 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, ensuring quality, consistency, and structure for AI tools and agents Drive adoption of AI capabilities (Looker agents, Hex AI) and integrate emerging AI tools into data team workflows Establish data governance standards, 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 Partner directly with director-level stakeholders on data strategy and architecture WHAT YOU BRING

15+ years of IT experience, including extensive data engineering and platform work, with 5+ years at a senior or lead level Expert-level proficiency in SQL, Python for data engineering, and data modeling fundamentals (dimensional, SCD, fact/dimension design) Deep expertise with the modern data stack: GCP, BigQuery, dbt, Fivetran, Airbyte, Looker, Hex, and orchestration tools (Dagster, Airflow) Strong infrastructure-as-code background, particularly with Terraform on GCP Hands-on experience integrating AI capabilities into analytics platforms (e.g., Looker agents, Hex AI) Experience owning and managing 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 Ability to define and evolve data architecture roadmaps and set technical standards for data modeling and platform integration Strong communication skills for translating business requirements into technical deliverables and partnering with executive stakeholders Experience mentoring and growing team members in data platform engineering, data modeling, and BI development practices Proven ability to drive cost optimization and operational excellence across data platforms

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