Data Analyst | Microsoft Fabric & Power Bi (Microsoft Fabric)

Peter Millar•Durham, NC

About The Position

The Data Analyst (Entry Level) – Microsoft Fabric & Power BI supports the build-out, QA, and rollout of enterprise Fabric data products and Power BI semantic models while also responding to day-to-day analytical requests from business partners. This role is ideal for someone who is curious, analytically minded, and eager to grow hands-on skills in governed self-service BI helping ensure data products are trusted, usable, and adopted across teams.

Requirements

Bachelor’s degree in Analytics, Economics, Finance, Statistics, Computer Science, or related field.
0–2 years of experience through internships, co‑ops, or full‑time roles in analytics, BI, or reporting (or equivalent project work).
Demonstrated exposure to Power BI or similar BI tools through coursework or professional experience.
Power BI fundamentals (visuals, filters, interacting with existing models).
Excel proficiency for analysis and reconciliation.
Introductory SQL (queries, joins, aggregations).
Intro familiarity with DAX measures and time intelligence.
Interest in analytics governance, semantic modeling, and enterprise BI patterns.

Responsibilities

Support the development and testing of Power BI / Fabric semantic models, including validating measures, dimensions, and business logic under direction of senior analytics engineers.
Assist in ensuring semantic models are well‑documented, consumer‑friendly, and standards‑aligned (clear naming, descriptions, and metadata).
Participate in model QA and release readiness, helping confirm that core metrics reconcile to expected results prior to broader rollout.
Follow established workspace, dataset, and governance standards to support scalable and trusted analytics delivery.
Build and maintain Power BI reports and dashboards using approved semantic models rather than bespoke logic.
Respond to ad‑hoc and recurring analytical requests by translating business questions into scoped analyses, visuals, or summaries.
Identify basic trends, anomalies, or performance drivers and escalate findings to senior team members as appropriate.
Support documentation of KPI definitions, metric logic, and usage guidance to reinforce a single source of truth.
Learn and apply data privacy and data handling standards embedded in analytics workflows.
Serve as a first line of support for “level 1–2” analytics questions, helping users navigate reports, Filters vs. measures, and basic interpretation.
Support rollout and onboarding activities (office hours, quick reference guides, “how to use the model” documentation).
Reinforce self‑service best practices and help direct users back to governed data products.