Lead Data Platform Engineer

H&R Block

1d•Remote

About The Position

Our Data Platforms team is building scalable, secure, and intelligent infrastructure to support advanced analytics, real-time insights, and seamless data integration. We are creating a unified data foundation that accelerates innovation and drives measurable business impact. As a visionary Lead Data Platform Engineer to architect, you will evolve, and lead our next-generation AI and data ecosystem. This is a hands-on leadership role that blends technical depth, strategic thinking, and shaping the technical vision of a modern data, data analytics, AI, and ML platforms. You’ll drive the design, development, and optimization of our enterprise data platform, integrating Power Platforms, Microsoft Fabric components with modern cloud-native and AI-driven technologies.

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.

Nice To Haves

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.
Certifications in Azure Data Engineering, Azure ML and Microsoft Fabric.

Responsibilities

Design and deliver scalable data AI platform solutions using Microsoft Fabric, Data Lake, SHIR, Power BI, Fabric-native services and Power Platforms.
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.
Migrate legacy systems to cloud-native and AI-enabled architectures, ensuring performance, reliability, and cost-efficiency.
Collaborate with analytics, visualization, engineering, and business teams to deliver reusable data assets, semantic models, and self-service capabilities.
Work with domain teams to decentralize data ownership and promote self-service capabilities that include data and AI services.
Establish and enforce standards for data quality, lineage, security, and monitoring.
Provide technical leadership, coaching, and career development for data engineers and platform developers.
Work closely with product managers, business leaders and vendors to prioritize and deliver high-value outcomes.