Principal Software Engineer

RBGlobal•Westchester, IL

16d•$171,290 - $256,990

About The Position

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.

Requirements

Extensive hands-on experience as a senior or principal-level data engineer, with a track record of designing and building production data platforms at scale.
Deep expertise across the Azure BI / data technology stack, including: Microsoft Fabric, Azure Synapse Analytics, Power BI and semantic modeling, 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 (testing, version control, CI/CD, modular design).
Working understanding of how data scientists consume data, enough to build the pipelines and feature/data infrastructure that support model training and serving.
Demonstrated ability to solve ambiguous, complex business problems through robust technical design and pragmatic execution.
Strong mentoring and influence skills — able to elevate engineering practices and lead technically without formal authority.
Excellent communication skills; able to explain complex technical concepts and tradeoffs to both technical and non-technical partners across Ops, Business, Sales, Marketing, Product, and Engineering.
Ability to thrive in a fast-paced, high-visibility environment with multiple priorities and stakeholders.

Nice To Haves

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

Responsibilities

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, and scalability challenges across BI and data workloads (e.g., Power BI, Synapse, Fabric).
Drive technical strategy and execution across Microsoft Fabric, Synapse, Power BI, and broader Azure BI technologies, evaluating new tools and making build/buy recommendations.
Mentor and grow data engineers and analytics engineers, conducting design reviews and elevating the technical capability of the team.
Act as a senior technical thought partner to engineering and business leadership on data architecture, technical tradeoffs, and platform investment priorities.
Translate complex business problems into practical, scalable, and well-architected data solutions.