Senior Analytics Engineer

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Summary We are a small team of analytic practitioners inside Information Systems, and we serve the entire university — academic units, enrollment, advancement, finance, HR, and student life. Some weeks that means sitting with a stakeholder to shape how their data should be structured. Other weeks it means building the pipeline, the model, and the dashboard end to end. Nobody on this team hands work over a wall. You will meet the stakeholder, understand the problem, design the solution, build it, and stay with it through adoption. If that scope sounds like a lot, it is — and it's the reason the work is interesting. We are also in the middle of a genuine platform shift. We're moving from a legacy reporting estate toward a modern lakehouse architecture on AWS and Microsoft Fabric, and replacing low-code integration with spec-driven development in Python. Alongside that, we're early in our AI journey — deliberately so. We have projects scoped and moving forward now, and we're working out what AI actually changes about this craft, from AI-assisted engineering through to agentic analytics for our stakeholders. We're not promising you a mature AI practice to plug into. We're offering something better: a chance to help build one. What we offer ● A small team where your work is visible and your judgment matters ● Room to shape a platform migration rather than maintain a finished one ● Real support for learning — training, certification, and time to explore new tools ● Flexibility in how you work: hybrid by default, with roughly one day a week on campus ● The breadth of a university: no two stakeholder problems look alike Job Description Partner with the institution ● Work directly with stakeholders across campus to understand their questions before defining a solution — requirements gathering is a conversation, not a ticket. ● Advise on data architecture, data management, and governance practices for units building their own capability. ● Coach and support customers through implementation and adoption. Service is a core part of this job, not an afterthought. Build the solutions ● Design and develop data pipelines, models, and analytic products spanning our source systems — Workday (SIS, Finance, HCM) among them. ● Write the SQL that does the heavy lifting: complex, performant, and readable enough that the next person can maintain it. ● Build and tune curated data layers in AWS Lake Formation/Athena and Microsoft Fabric, and deliver reporting through Power BI and other analytic tools. ● Own solutions through the full lifecycle — discovery, design, build, test, deploy, support, iterate. Modernize the platform ● Help move our integration work from SnapLogic toward spec-driven development in Python using AI-assisted tooling. ● Contribute to decisions on our future warehouse direction, including evaluation of Redshift and Snowflake. ● Help retire legacy reporting (Cognos) responsibly,