Principal Data Platform Engineer

Blue Yonder • Scottsdale, AZ

4d • $155,000 - $172,873 • Remote

About The Position

Blue Yonder is seeking a Principal Data Platform Engineer to own the platforms our data and AI capabilities run on, Power BI, AtScale, and Databricks. As Blue Yonder deploys an AI-first operating model, these platforms are the critical foundation for how the enterprise sees, decides, and acts. Their performance, reliability, and accessibility are functions this role owns outright. This is a deeply technical senior individual contributor role. The successful candidate pairs hands-on platform administration and engineering depth with the judgment to make architecture, cost, and governance decisions that hold up at enterprise scale, and the credibility to set standards across a large data organization without formal authority. Outcomes in this role are visible to executive leadership and felt by every user of the platform.

Requirements

• 8+ years in data platform engineering, platform administration, analytics engineering, or a closely related discipline.
• 5+ years of hands-on experience administering and engineering enterprise cloud data platforms, including Databricks and Azure, with demonstrated responsibility for production environments, security, performance, reliability, and cost optimization.
• 5+ years of hands-on experience administering enterprise analytics and semantic platforms, including Power BI and comparable semantic layer technologies, supporting hundreds of production assets and 1,000+ users.
• Demonstrated ownership of production data platforms serving a large, distributed user base where downtime is immediately visible
• Proven track record of delivering measurable cost optimization on cloud data and analytics platforms
• Experience establishing governance and technical standards across multiple tools and competing stakeholder groups
• Experience managing enterprise software vendors, including support escalation and input into renewals
• History of operating as the most senior technical authority on a platform without direct reports
• Expert-level administration of Databricks: Unity Catalog, cluster policies, SQL warehouses, identity and workspace configuration, and cost controls
• Deep tenant and capacity administration experience with Power BI: capacity management, gateways, workspace architecture, and deployment pipelines
• Hands-on experience administering a semantic layer platform; AtScale strongly preferred
• Strong working knowledge of Azure: Identity (Entra ID), networking, storage, private endpoints, and cost management
• Expert-level SQL for troubleshooting, performance tuning, and usage analysis
• Python and/or PowerShell for platform automation, API-driven administration, and reporting; comfort with version control, CI/CD, and infrastructure-as-code
• Experience with SSO, SAML/OAuth, service principles, role-based access control, and data-level security models
• Practical experience configuring and governing enterprise AI tooling, connectors, MCP server connections, agent and assistant configuration, and the access boundaries around them

Nice To Haves

• Microsoft Fabric: Experience with Fabric architecture, capacity models, and migration from standalone Power BI Premium
• FinOps: Formal FinOps practice experience or certification, applied to cloud data platform spend
• AI Governance: Experience standing up governance for enterprise AI tooling—acceptable use, data access boundaries, logging, and retention
• Agentic Integration: Hands-on experience building or operating MCP servers and agent integrations against enterprise data sources (significant advantage)
• Observability: Experience with platform observability tooling such as Azure Monitor, Grafana, or Datadog
• Certifications: Databricks Certified Data Engineer Professional, Azure Solutions Architect Expert, or equivalent
• Transformation Experience: Experience supporting an organization through an AI-first transformation, where adoption grew faster than the platform was originally sized for
• Industry: Prior experience in supply chain, logistics, or enterprise software

Responsibilities

• Own the day-to-day administration, configuration, and health of the enterprise data and AI platform estate: Power BI, AtScale, Databricks, Microsoft Copilot, and Claude
• Administer Databricks workspaces, cluster policies, SQL warehouses, Unity Catalog, service principals, and workspace-level security
• Manage the Power BI tenant end to end—tenant settings, capacity, workspace architecture, data gateways, and deployment pipelines
• Administer AtScale, including semantic model deployment, catalog and environment management, aggregate strategy, and query engine tuning
• Manage the enterprise AI platform layer—entitlement and seat administration, workspace and project structure, and enablement of new capabilities as they ship
• Define and run upgrade, patch, and release management processes; test and roll out platform changes without disrupting users
• Own platform availability and performance; serve as the senior escalation point for platform-level incidents
• Establish monitoring, alerting, and observability across the estate, including performance baselines and capacity headroom tracking
• Diagnose complex problems that span identity, network, compute, and semantic layers, driving them to root cause rather than symptom relief
• Act as the key point of contact for the data team and business end users across all platforms—triage, resolution, and follow-through
• Build runbooks, self-service documentation, and enablement material that reduce recurring support demand
• Own the cost model for the platform estate: capacity sizing, compute policies, autoscaling behavior, SKU selection, licensing, and consumption-based AI spend
• Identify and eliminate waste—idle compute, oversized capacity, unused licenses, inefficient queries, and redundant refresh schedules
• Build showback and chargeback reporting so business units can see and be accountable for their own consumption
• Forecast platform spend, partner with Finance on budget planning, and quantify the return on platform investment
• Implement and enforce governance across platforms: access models, role-based and row-level security, workspace and catalog standards, and content certification processes
• Own governance of the AI layer—which data AI tools may reach, which connectors and integrations are approved, and how usage is logged, retained, and audited
• Partner with Security, IT, and Legal on data residency, data loss prevention, audit, and regulatory requirements
• Maintain the authoritative documentation set for the platform: standards, architecture decisions, and configuration baselines
• Configure and maintain integrations across the estate, including MCP server connections, cross-platform connectivity, single sign-on, service principals, and API and gateway configuration
• Evaluate, pilot, and productionize new platform capabilities, connectors, and integration patterns, including the AI tooling that increasingly depends on them
• Manage environment promotion across development, test, and production, applying infrastructure-as-code and version control where practical
• Instrument and report on platform usage—active users, workload patterns, adoption by team, AI tool utilization, and license efficiency
• Convert usage data into recommendations: where to invest, where to consolidate, and where enablement is needed
• Deliver recurring reporting on platform health, cost, adoption, and risk to data leadership and executive stakeholders
• Serve as the primary technical relationship owner for platform vendors, including Microsoft, Databricks, AtScale, and Anthropic
• Manage support escalations, roadmap reviews, and participation in early-access and preview programs
• Provide the technical input that shapes renewals, licensing structures, and commercial negotiations
• Hold vendors accountable to service levels, defect resolution, and committed roadmap
• Advise the leader of Enterprise Data Engineering on platform strategy, build-versus-buy decisions, and multi-year architecture direction
• Set the technical standards other engineers work too, influencing through demonstrated expertise rather than reporting lines
• Represent the platform in enterprise architecture, security review, and AI governance forums
• Mentor engineers, analysts, and business users on getting the most out of the platform

Benefits

• Comprehensive Medical, Dental and Vision
• 401K with Matching
• Flexible Time Off
• Corporate Fitness Program
• A variety of voluntary benefits such as; Legal Plans, Accident and Hospital Indemnity, Pet Insurance and much more

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed