Analytics Engineer (Power BI Specialist)

Analytics Engineer (Power BI Specialist) Company overview: Blue Orange Digital is a boutique data & AI consultancy that delivers enterprise-grade results. We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market and enterprise clients across Private Equity, Financial Services, Healthcare, and Retail. Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ecosystem to turn messy, real-world data into trustworthy, actionable insight. We’re a builder‑led, client‑first culture that prizes ownership, clear communication, and shipping high‑impact work. Note: Please submit your resume in English, as all application materials must be in English for review and consideration. Position Overview Blue Orange Digital is seeking a Senior Analytics Engineer and Power BI Specialist to own the analytics and visualization layer of a 26‑week enterprise data warehouse implementation in the global commodities trading and supply chain industry. You will join full‑time from Week 6 through Week 22, designing and building Fabric Semantic Models and production Power BI reports that translate Gold‑layer data products into operational dashboards for trading, risk, and finance stakeholders — including Trader P&L, Global Position, Risk Metrics (VaR), and Financial Consolidation. This role bridges the engineering team and business users, requiring deep Power BI expertise and the communication skills to work directly with trading and finance professionals. Responsibilities Design and build Microsoft Fabric Semantic Models (Power BI datasets) on top of Gold‑layer Lakehouse and Warehouse data products Define DAX measures, hierarchies, relationships, and semantic model structures Develop production Power BI dashboards for Trader P&L, Global Position, VaR, and Financial Consolidation Work directly with trading, risk, and finance stakeholders to translate reporting requirements into semantic model design Optimize DirectQuery and Import mode performance for complex financial and trading datasets Define naming conventions, metric hierarchies, and semantic governance standards for the Fabric workspace Collaborate with Data Engineers to ensure Gold‑layer outputs are analytics‑ready Support self‑service analytics enablement for client analysts Contribute to UAT, report validation, and business sign‑off on accuracy and performance Requirements 7+ years in analytics engineering, BI development, or data analytics with production‑grade Power BI delivery Deep hands‑on expertise with Power BI (semantic models, DAX, report design, workspace management, RLS) Experience with Microsoft Fabric Power BI integration or SSAS/AAS as a semantic layer Strong SQL for analytical queries and metric logic Proven ability to engage finance, trading, or risk stakeholders and translate requirements into technical specifications Bachelor’s degree in a quantitative, technical, or analytical field (or equivalent experience) Preferred Qualifications Exposure to commodity trading, financial risk, or P&L reporting environments Microsoft Power BI certification (PL‑300 or PL‑400) Hands‑on experience with DAX optimization and performance tuning for large tabular models Familiarity with Fabric Lakehouse/Warehouse as semantic model sources (DP‑600 or DP‑700 exposure a plus) Salary: $ 5,500 - 7,200 [ USD ] monthly Background checks may be required for certain positions/projects. Blue Orange Digital is an equal-opportunity employer. Department Engineering Role Data Analyst Locations Remote - Europe, Berlin, Cracow, Kyiv, Lisbon, London, Rome, Warsaw Remote status Fully Remote Monthly salary $5,500 - $7,200 About Blue Orange Digital Blue Orange Digital is a data and AI consulting firm that helps companies turn complex data into real business outcomes. We partner with organizations across industries to design and deploy scalable data infrastructure, advanced analytics, and AI-powered solutions. Our team is fully remote, globally distributed, and driven by curiosity, impact, and innovation.