Senior Staff Data Engineer
Chicago, IL, United States
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
Remote — work setting source
Work setup in the employer’s posting: Remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingIAA is seeking a Senior Staff Data Engineer to be a senior individual contributor and technical leader within our data engineering function.
The Senior Staff Data Engineer 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.
Design and build major data systems, pipelines, and reusable components
Deliver complex data work across ingestion, transformation, storage, and data delivery on Azure
Build production data pipelines and feature infrastructure for data scientists
Diagnose and resolve performance and reliability issues across BI and data workloads
Mentor data and analytics engineers through design and code reviews
From the employer’s posting
IAA is seeking a Senior Staff Data Engineer to be a senior individual contributor and technical leader within our data engineering function. This is a hands-on, deeply technical role for an engineer who designs and builds complex, business-critical components of IAA’s data platform, drives architectural decisions within their area, and raises the engineering bar across the team.
The Senior Staff Data Engineer 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. This person leads through technical depth, strong execution, and influence rather than headcount, acting as a multiplier for the engineers around them.
Design and build major data systems, pipelines, frameworks, and reusable components
Personally deliver complex, high-impact data engineering work on IAA’s Azure data and analytics stack
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
Mentor data engineers and analytics engineers, conducting design reviews
What you’ll bring
All qualificationsCore experience
- Extensive hands-on experience as a senior or staff-level data engineer
- Deep expertise in Microsoft Fabric, Azure Synapse, and Power BI
- Expert-level Python and SQL with solid software engineering practices
- Strong data architecture and dimensional and semantic modeling skills
Preferred experience
- 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 contributing to platform-wide standards and reference architectures used across multiple teams.
Qualification wording
Extensive hands-on experience as a senior or staff-level data engineer
Deep expertise across the Azure BI / data technology stack, including:
Expert-level proficiency in Python and SQL, with strong software engineering fundamentals (testing, version control, CI/CD, modular design)
Strong command of data engineering architecture, modern analytics platforms, dimensional and semantic modeling
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 contributing to platform-wide standards and reference architectures used across multiple teams.
Tools in this posting
- Python
- SQL
- Azure
- Power BI
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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
- Microsoft Fabric - Azure Synapse Analytics - Power BI and semantic modeling
- 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.
- 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.
- Azure Synapse Analytics - Power BI and semantic modeling - Broader Azure data and analytics services
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · today
- Recorded sightings
- 4
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
IAA is seeking a Senior Staff Data Engineer to be a senior individual contributor and technical leader within our data engineering function. This is a hands-on, deeply technical role for an engineer who designs and builds complex, business-critical components of IAA’s data platform, drives architectural decisions within their area, and raises the engineering bar across the team.
The Senior Staff Data Engineer 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. This person leads through technical depth, strong execution, and influence rather than headcount, acting as a multiplier for the engineers around them.
This role partners closely with engineering leadership, data scientists, BI developers, platform/infrastructure teams, and business stakeholders across Operations, Sales, Marketing, and Product.
- 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.
- 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.
- 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 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.
The Senior Staff Data Engineer is a key technical leader within IAA’s data engineering organization. This person builds and scales the systems that enable better decisions, improved business performance, operational efficiencies, and a durable competitive advantage. Through hands-on engineering, strong design, and influence, this role directly impacts both technical direction and business outcomes across the organization.
Source details
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- Pay
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- Location & working pattern
Chicago, IL, United States
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