Data Engineer

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* JOB DESCRIPTION:

** The Staff Data Engineer is a senior, hands-on technical contributor within an Enterprise Data domain, owning technical design and the most complex implementation work for assigned data products, capabilities, and integrations. The role establishes, communicates, and evolves the technical approach for the work it leads and is accountable for the quality, durability, and supportability of the solutions it shapes.

Staff Data Engineers work directly with business stakeholders to understand needs and shape technical solutions, engaging at a level appropriate to the work they lead. The role is expected to be fluent in both technical execution and business context, translating between them without losing precision in either.  The Staff Data Engineer sets technical direction for assigned capabilities and initiatives within the domain, applies enterprise standards and platform patterns, engages Principal Engineers where cross-domain considerations apply, and multiplies the effectiveness of the domain team through design leadership, code review, and mentoring.

** This role is based in Madison, WI**.  Essential Duties Include, but are not limited to, the following:
** Technical design and solutioning
*** Own technical design and hands-on delivery for the most complex or highest-risk work across assigned data products, capabilities, and initiatives, including data models, pipeline architecture, integration patterns, and platform usage decisions.
* Produce design documentation that allows others to understand, review, and build on technical decisions, and drive design review with domain and cross-domain peers.
* Build and evolve assigned domain data products so they are documented, discoverable, governed, observable, and supported throughout their lifecycle for reuse across analytics, semantic layers, machine learning, and AI applications.
* Define and uphold data contracts for the products the domain publishes, including schemas, freshness and availability expectations, breaking-change policy, and producer and consumer responsibilities.
* Design data products for AI and machine learning consumption with reproducibility, lineage, timeliness, and defined data quality controls appropriate to the use case.
* Diagnose and resolve complex production and data quality issues, and drive root cause resolution rather than recurring remediation.
* Use approved AI-assisted development tooling where appropriate to accelerate engineering work, validating output against correctness, security, privacy, and quality standards.
* Own the technical cost efficiency of assigned data products, including compute and warehouse sizing, job and query optimization, serverless and storage tradeoffs, and cost-to-serve implications.
* Evaluate and recommend tools, patterns, and platform capabilities within enterprise standards, raising cases where an exception may be warranted.
** Stakeholder engagement
*** Work directly with business stakeholders to understand needs, clarify requirements, and shape technical solutions.
* Communicate technical concepts, tradeoffs, constraints, and delivery implications clearly to non-technical audiences.
* Participate in technical working sessions with partner organizations such as Software Engineering, IT Applications, and Enterprise Architecture on integration and design questions affecting the domain.
* Surface scope, priority, resourcing, and technical-debt implications of technical decisions for leadership review rather than resolving them independently.
** Technical leadership and multiplication
*** Serve as a technical lead for assigned domain capabilities and initiatives, guiding engineers through design and implementation without formal authority.
* Provide code and design…