Senior Staff Software Engineer
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Job Description
Senior Staff Data Engineer at IAA designing and delivering complex data systems and analytics. Partnering with leadership and mentoring engineers to improve technical capabilities.
Responsibilities:
- Design and build major data systems, pipelines, frameworks, and reusable components, owning architecture within your area and contributing to platform-wide design alongside the Director Data Engineering.
- Personally deliver complex, high-impact data engineering work on IAA’s Azure data and analytics stack — ingestion, transformation, storage, semantic modeling, and data delivery.
- Apply and help refine engineering standards and patterns across code quality, performance, scalability, observability, and governance, and drive their adoption through example and code/design review.
- Build 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 difficult performance, reliability, and scalability challenges across BI and data workloads (e.g., Power BI, Synapse, Fabric).
- Contribute to technical strategy across Microsoft Fabric, Synapse, Power BI, and broader Azure BI technologies, helping evaluate new tools and inform build/buy decisions.
- Mentor data engineers and analytics engineers, conducting design reviews and helping elevate the technical capability of the team.
- Serve as a technical partner to engineering leadership on data architecture and technical tradeoffs within your scope.
- Translate complex business problems into practical, scalable, and well-architected data solutions.
Requirements:
- Extensive hands-on experience as a senior or staff-level data engineer, with a track record of designing and delivering production data systems 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 problems through robust technical design and pragmatic execution.
- Strong mentoring and influence skills — able to elevate engineering practices and lead technically within a team.
- 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.
Benefits:
- Medical, dental, vision, and basic life insurances.
- 401k plan with 100% matching for the first 4% contributed.
- 15 days of PTO each year.
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