Data Systems Analyst (D365 F&O, Azure Synapse, Fabric)

Job Description

<p>PrecisionERP / PrecisionIT is seeking a qualified Data Systems Analyst to work with our client's D365 program. We’re seeking a hands-on consultant who blends data engineering, analytics, and applied data science to accelerate enterprise reporting and planning automation.</p><p><br></p><p>You will be the technical backbone across <b>D365 F&O, Synapse Link, BPA/BPP, Azure Synapse, and Fabric</b>—designing robust pipelines, models, and reports that advance our maturity from <b>diagnostic to predictive/prescriptive</b> analytics.</p><p><br></p><p>D365 program is moving reporting from on-premises to Fabric plus D365 F&O data platform. With D365 Microsoft Business Performance Planning (BPP) and Business Performance Analytics (BPA) on top and Synapse Link plus Microsoft Fabric as the core.</p><p><br></p><p><b>Contract duration:</b> 6 months with potential for extension</p><p><br></p><p><b>Federal clearance eligibility will be required</b></p><p><br></p><p><b>Tasks: </b></p><p><br></p><p><b>D365 & Synapse Link</b></p><ul><li>Configure and optimize <b>D365 F&O → Azure Synapse Link</b> (tables, change feeds, performance, known limitations).</li><li>Ensure reliable replication to <b>Data Lake / Fabric Lakehouse</b>; validate schemas, keys, and deltas.</li></ul><p><br></p><p><b>Fabric & Azure Synapse Engineering</b></p><ul><li>Build ELT pipelines in <b>Fabric (Dataflows Gen2, Pipelines), Lakehouse/Warehouse, Spark/SQL</b> and/or <b>Azure Synapse</b>.</li><li>Model conformed/serving layers for Finance, Operations, and Commerce domains.</li><li>Implement <b>Direct Lake</b> and <b>Import/Composite</b> models as appropriate.</li></ul><p><br></p><p><b>BPA/BPP Reporting & Planning</b></p><ul><li>Partner with Finance to deliver <b>BPA reports</b> and <b>BPP cubes/workflows</b> (budgeting/forecasting, departmental roll-ups).</li><li>Develop high-complexity financial reports (P&L by dimensions, contribution margin, variance/driver analysis).</li></ul><p><br></p><p><b>Analytics & Data Quality</b></p><ul><li>Prepare/transform data for analysis; create <b>Power BI</b> datasets, measures (DAX), and visuals for decision-making.</li><li>Apply <b>statistical/ML methods</b> (forecasting, A/B testing) where they add clear value.</li><li>Document data flows, definitions, lineage, and metadata in the <b>data catalog</b>; contribute to governance and continuous improvement.</li></ul><p><br></p><p><b>DevOps & Ways of Working</b></p><ul><li>Use <b>Azure DevOps</b> for user stories, CI/CD (Power BI/Fabric), testing, and release management across <b>DEV/TEST/PROD</b>.</li><li>Support UAT, cutover readiness, and knowledge transfer to internal teams.</li></ul><p><br></p><p><b>Requirements: </b></p><ul><li>5+ years in data engineering/BI with <b>D365 F&O</b> exposure and at least one production <b>Synapse Link for D365</b> implementation.</li><li>Strong SQL (T-SQL/Spark SQL), data modeling (star/schema for finance), and ELT on <b>Fabric</b> and/or <b>Azure Synapse</b>.</li><li>Hands-on <b>Power BI</b> (Power Query, DAX, model security), including performance tuning and enterprise deployment patterns.</li><li>Practical experience with <b>BPA/BPP</b> (or equivalent EPM tools) supporting budgeting/forecasting workflows and financial reporting.</li><li>Version control and CI/CD (Azure DevOps), environment promotion, and testing practices.</li><li>Excellent communication with Finance/Operations/Commerce stakeholders and IT—able to explain trade-offs and document clearly.</li></ul><p><br></p><p><b>Nice to have (Assets)</b></p><ul><li>Experience with <b>Direct Lake</b> semantic models and <b>Fabric Warehouse vs. Lakehouse</b> design choices.</li><li>Python/PySpark for transformations; performance tuning of large fact tables/slowly changing dimensions.</li><li>Data governance tools (e.g., <b>Purview</b>) and KPI/metrics standardization.</li><li>Forecasting methods (classical time series or ML) applied to finance, commence, and operations datasets.</li><li>Public-sector or Crown corporation experience.</li></ul><p></p>