Lead Data Platform Engineer

H&R Block is a leader in tax preparation and financial services, dedicated to helping clients and communities. They are seeking a Lead Data Platform Engineer to architect and lead their next-generation AI and data ecosystem, focusing on building scalable and secure data platforms that empower decision-making across the enterprise.

Responsibilities:

• Architect & Build: Design and deliver scalable data AI platform solutions using Microsoft Fabric, Data Lake, SHIR, Power BI, Fabric-native services and Power Platforms
• Lead Initiatives: Drive end-to-end implementation of data projects, from ingestion and transformation to governance, observability, and consumption. Ensure high standards of data reliability, security, and performance
• Modernize Infrastructure: Migrate legacy systems to cloud-native and AI-enabled architectures, ensuring performance, reliability, and cost-efficiency
• Enable Data & AI Products: Collaborate with analytics, visualization, engineering, and business teams to deliver reusable data assets, semantic models, and self-service capabilities
• Promote Data Mesh Principles: Work with domain teams to decentralize data ownership and promote self-service capabilities that include data and AI services
• Champion Best Practices: Establish and enforce standards for data quality, lineage, security, and monitoring
• Mentor & Guide: Provide technical leadership, coaching, and career development for data engineers and platform developers
• Cross-Functional Partnership: Work closely with product managers, business leaders and vendors to prioritize and deliver high-value outcomes

Requirements:

• 7+ years of proven experience designing, implementing, and leading enterprise-scale data platforms
• Deep expertise in Microsoft Fabric, Azure Data Services and modern data and AI architecture patterns
• Strong proficiency in SQL, Python and data modeling techniques
• Familiarity with CI/CD pipelines, DevOps for data, ML Ops practices, and infrastructure-as-code
• Excellent communication and stakeholder management skills
• Demonstrated ability to lead small teams while remaining hands-on with complex technical challenges
• Bachelors degree in a related field or the equivalent through a combination of education and related work experience
• Masters degree in a related field or the equivalent through a combination of education and related work experience
• Certifications in Azure Data Engineering, Azure ML and Microsoft Fabric
• Exposure to machine learning pipelines or advanced analytics
• Advanced (applied theory) Develop and deploy new tools to help protect, govern, validate and maintain the data sources used by the data science and analytics team
• Advanced (applied theory) Experience Applying ML to data engineering problems
• Experience with OneLake, Lakehouse architecture, and Fabric-native governance tools
• Knowledge of data mesh principles and domain-oriented data ownership