Analytics Engineer

• Collaborate with stakeholders to understand business requirements and translate them into scalable and efficient data analytics solutions.
• Possess in-depth knowledge and hands-on experience with Microsoft Fabric ecosystem (Lakehouse, PySpark/SQL notebooks, data pipelines, and deployment pipelines).
• Understanding Microsoft Dynamics as a data source a big plus.
• Design data models that bridge the Fabric Lakehouse, Power BI semantic models, and reporting layers, ensuring consistency between raw, curated, and business-facing data.
• Optimize data models to support efficient data storage, retrieval, and analysis, ensuring data integrity, accuracy, and reliability.
• Knowledge of Fabric capacity (CU) optimization a big plus.
• Implement data integration pipelines using Microsoft Fabric and other relevant tools to extract, transform, and load data from various sources into a unified data platform.
• Create visually appealing and interactive dashboards, reports, and visualizations using Microsoft Power BI and DAX language, enabling users to gain valuable insights from data.
• Identify performance bottlenecks and implement optimizations to improve data processing, query performance, and overall system efficiency.
• Collaborate with cross-functional teams, providing technical leadership and guidance to data engineers, analysts, and other stakeholders to ensure successful project delivery.
• Keep abreast of the latest advancements in data analytics technologies (Microsoft based and others) and industry trends, continuously enhancing your expertise and applying best practices in solution design and implementation.

Data Analytics Engineer

• Design and maintain production-grade Microsoft Fabric semantic models that serve as the single source of truth for enterprise metrics
• Define, document, and enforce KPI and metric definitions in collaboration with operational and finance stakeholders
• Build clean, reusable DAX measures and optimized data model relationships across fact and dimension structures
• Design and deliver analysis-ready data structures that translate warehouse data into formats optimized for reporting and decision-making
• Partner with data engineers to align pipeline outputs with semantic layer requirements, ensuring data arriving from upstream processes meets the structure and quality needed for governed reporting
• Establish and enforce naming conventions, measure governance standards, and row-level security patterns
• Audit available operational datasets against business decision needs, identifying gaps and defining requirements for upstream pipeline development.
• Manage the lifecycle of metric definitions including versioning, deprecation, and change communication to downstream report consumers.
• Document semantic models and provide guidance to Power BI developers consuming them
• Stay current with the Microsoft Fabric and Power BI ecosystem and help shape platform evolution.

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Data Analytics Engineer

Analytics Engineer