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Principal Software Engineer

RBGlobal•United States•🌍 Remote
Full-timeSenior
👁️ 0 views•📝 0 applications•Posted 9/29/2026•Expires 10/30/2026
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Job Description

About the Role IAA is seeking a Principal Data Engineer to serve as the most senior individual contributor and technical authority across our data engineering function.

This is a hands-on, deeply technical leadership role for an engineer who sets architectural direction, raises the engineering bar, and personally builds the most complex and business-critical components of IAA’s data platform.

Where the Director leads through people and strategy, the Principal Data Engineer leads through technical depth, influence, and execution. This person defines patterns and standards, solves the hardest data engineering problems, and acts as a force multiplier for engineers across the organization.

They ensure IAA’s data platform is scalable, reliable, secure, and ready to power advanced analytics, BI, forecasting, and the data needs of AI solutions.

This is a high-visibility role that partners closely with engineering leadership, data scientists, BI developers, platform/infrastructure teams, and business stakeholders across Operations, Sales, Marketing, and Product.

What You’ll Do Set and evolve the technical architecture for IAA’s data platform — ingestion, transformation, storage, semantic modeling, and data delivery — on the Azure data and analytics stack.

Personally design and build the most complex, high-impact data pipelines, frameworks, and reusable components that other engineers build upon.

Define engineering standards and patterns across architecture, code quality, performance, scalability, observability, and governance — and drive their adoption through example and mentorship.

Lead the design and implementation of robust pipelines, semantic models, and data products that power dashboards, self-service analytics, forecasting, and downstream machine learning systems.

Build the production-grade data pipelines and feature/data infrastructure that data scientists rely on to train, serve, and operationalize models. Diagnose and resolve the toughest performance, reliability

Required Skills

AzureData EngineeringData ArchitectureData PipelinesSemantic ModelingMachine Learning

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