Technology Financial Operations Data Analytics

Technology Financial Operations Data Analytics & BI Engineer Who we are looking for We are looking for a Technology Financial Operations Data Analytics & BI Engineer reporting to the Technology Financial Operations Office. This role builds and supports the data models, dashboards, pipelines. Why this role is important to us This is a build-and-support role: the successful candidate does the BI engineering and data modeling directly, works with the stakeholders who use the output, and stays with those products once they are in production. The work runs the full path from a loosely defined reporting request through discovery, data preparation, modeling, build, validation, release, and ongoing support. The work is to move recurring reporting off manual spreadsheets and one-off files and onto governed analytics products with reliable refreshes, consistent definitions, and clear ownership. Microsoft Power BI and Microsoft Fabric are the corporate platforms for this work; strong comparable enterprise BI experience will also be considered. Near-term work includes reporting for IT Total Cost of Ownership and showback, Cloud FinOps spend and optimization tracking, productivity and demand reporting, and the retirement of high-effort manual reports. What You Will Be Responsible For Build and maintain data pipelines, transformations, semantic models, dashboards, and refreshable reporting solutions using Microsoft Power BI, Microsoft Fabric, and related analytics tools. Modernize spreadsheet-based reporting by converting recurring, manually maintained reports into governed, reusable BI products with defined owners and a support model. Develop reporting that supports technology financial management, IT Total Cost of Ownership, Cloud FinOps, portfolio, demand, and headcount processes, including showback views and optimization tracking. Prepare, reconcile, and model data from finance, cloud, procurement, portfolio, headcount, and service management systems, including the transformation logic and refresh processes that keep those sources aligned. Build reusable datasets, semantic models, and measures, together with the validation checks and exception reporting that surface data quality issues before they reach a report. Design dashboards and reports that Business Office teams, finance partners, and senior technology leaders can read and act on without a walkthrough. Work directly with business stakeholders to capture requirements, agree definitions, and validate results, translating loosely defined questions into something the available data can answer. Apply controlled release, change, and access practices so reporting stays secure, traceable, and safe to change once it is in production. Document sources, definitions, assumptions, calculation logic, refresh schedules, and known limitations. Support delivered products after launch, including issue intake, triage, resolution, and continuous improvement. What We Value These skills will help you succeed in this role Ownership of a vague reporting request from discovery through build, validation, release, and ongoing support, including the unglamorous parts, without needing to be chased. Comfort working with imperfect source data, and the discipline to reconcile differences, document assumptions, and state plainly what the data will and will not support. A clear line between actuals, forecasts, estimates, and advisory analysis, held consistently and without turning every number into a caveat. The ability to explain a number, its limitations, and the tradeoffs behind it to a finance partner, a technical peer, or a senior executive. Comfort working across functions where definitions, source data, and ownership are still maturing, and the patience to build alignment rather than wait for it. A product mindset that treats reporting as a supported capability with an owner, a backlog, and a roadmap rather than a series of one-off builds. Exacting standards for documentation, data quality, governance, and auditability, because these reports are relied on every month and are expected to hold up to review. Education & Preferred Qualifications Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Finance, Business Analytics, Engineering, or a related field preferred; equivalent experience may be considered. Hands-on experience building BI solutions using Microsoft Power BI and Microsoft Fabric preferred, including Power Query, DAX, semantic models, dashboards, dataflows, lakehouse or warehouse patterns, and SQL; strong comparable enterprise BI experience will also be considered. Demonstrated experience building data models, measures, reconciliations, and refresh processes that span multiple source systems and survive routine change in those sources. Familiarity with financial, portfolio, procurement, cloud, and headcount data, and with IT cost transparency concepts such as Total Cost of Ownership, showback, and Cloud FinOps, preferre