Senior Staff Data Engineer

RBGlobal•Westchester, IL

1d•$142,530 - $178,110

About The Position

IAA is seeking a Senior Staff Data Engineer to serve as a senior individual contributor and technical leader in its data engineering function. This hands-on, deeply technical role designs and builds complex, business-critical components of IAA’s data platform, drives architectural decisions within its area, and raises engineering standards across the team. The role owns the design and delivery of major systems and data products, partners with the Director on platform-wide architecture and standards, and leads execution on significant, often ambiguous initiatives through technical depth, execution, and influence rather than headcount. The position works closely with engineering leadership, data scientists, BI developers, platform and infrastructure teams, and business stakeholders across Operations, Sales, Marketing, and Product. It delivers complex data engineering work across IAA’s Azure data and analytics stack, including ingestion, transformation, storage, semantic modeling, and data delivery. The engineer builds pipelines, semantic models, reusable components, and production-grade data and feature infrastructure for analytics, forecasting, dashboards, and machine learning, while helping shape technical strategy across Microsoft Fabric, Synapse, Power BI, and broader Azure BI technologies. RB Global is an omnichannel marketplace providing insights, services, and transaction solutions for buyers and sellers of commercial assets and vehicles worldwide. Its portfolio includes Ritchie Bros., IAA, Rouse Services, SmartEquip, Xcira, and Veritread. Full-time employees are offered medical, dental, vision, and basic life insurance, access to a 401(k) plan with a company match of 100% of the first 4% contributed, and 15 days of PTO each year.

Requirements

Extensive hands-on experience as a senior- or staff-level data engineer, with a record of designing and delivering production data systems at scale.
Deep expertise across the Azure BI and data technology stack, including Microsoft Fabric, Azure Synapse Analytics, Power BI and semantic modeling, and broader Azure data and analytics services.
Strong command of data engineering architecture, modern analytics platforms, dimensional and semantic modeling, and scalable, fault-tolerant pipelines.
Expert-level proficiency in Python and SQL, with strong software engineering fundamentals including testing, version control, CI/CD, and modular design.
Working understanding of how data scientists consume data, sufficient to build pipelines and feature/data infrastructure that supports model training and serving.
Demonstrated ability to solve ambiguous, complex problems through robust technical design and pragmatic execution.
Strong mentoring and influence skills, with the ability to elevate engineering practices and lead technically within a team.
Excellent communication skills and ability to explain technical concepts and tradeoffs to technical and non-technical partners across Operations, Business, Sales, Marketing, Product, and Engineering.
Ability to thrive in a fast-paced, high-visibility environment with multiple priorities and stakeholders.

Nice To Haves

Experience building data platforms for enterprise use cases across operations, commercial functions, and product-driven organizations.
Experience spanning BI modernization and data platform enablement for analytics and machine learning within the same platform.
Familiarity with cloud-native engineering practices, infrastructure as code, and secure, scalable data environments.
Experience contributing to platform-wide standards and reference architectures used across multiple teams.
Experience building data pipelines that support RAG, LLM, or modern AI workloads on enterprise data.

Responsibilities

Design and build major data systems, pipelines, frameworks, and reusable components; own architecture within the assigned area and contribute to platform-wide design alongside the Director of Data Engineering.
Personally deliver complex, high-impact data engineering work across IAA’s Azure data and analytics stack, including ingestion, transformation, storage, semantic modeling, and data delivery.
Apply and refine engineering standards and patterns for code quality, performance, scalability, observability, and governance, and encourage adoption through example and code and design reviews.
Build robust pipelines, semantic models, and data products for dashboards, self-service analytics, forecasting, and downstream machine learning systems.
Build production-grade data pipelines and feature/data infrastructure that data scientists use to train, serve, and operationalize models.
Diagnose and resolve difficult performance, reliability, and scalability challenges across BI and data workloads, including Power BI, Synapse, and Fabric.
Contribute to technical strategy across Microsoft Fabric, Synapse, Power BI, and broader Azure BI technologies; help evaluate tools and inform build-versus-buy decisions.
Mentor data engineers and analytics engineers, conduct design reviews, and help elevate the team’s technical capability.
Partner with engineering leadership on data architecture and technical tradeoffs within the role’s scope.
Translate complex business problems into practical, scalable, well-architected data solutions.