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Our Client is driving a large-scale digital transformation to modernize its global supply chain through an integrated, data-driven planning platform. The initiative focuses on core capabilities such as demand planning, supply and capacity planning, replenishment, and sales forecasting, delivered through multiple Agile delivery streams. As a Power BI Engineer, you will be focused on transforming raw data into reliable, accurate, and user-friendly dashboards, reports, and self-service semantic models. You will bridge the gap between data engineering and analysis by ensuring data products are technically sound, visually intuitive, and aligned with business objectives. The ideal candidate is a visualization expert, highly curious, and collaborative — someone who enjoys solving complex data problems and communicating insights clearly to both technical and business stakeholders.
Job Responsibility:
Design, develop, and maintain Power BI dashboards, reports, and data models
Transform raw data into structured, meaningful datasets suitable for self-service analytics
Ensure data quality, usability, and accessibility across all analytical assets
Collaborate with data engineers, business analysts, and stakeholders to align solutions with business needs
Apply best practices in data visualization to effectively communicate insights and tell compelling data stories
Document solutions, validations, and processes to ensure reproducibility and maintainability
Requirements:
3+ years of hands-on experience with Power BI
Proficiency in SQL, Tabular modeling, and DAX Studio for building and optimizing analytical models
Experience in data modeling and building semantic models for self-service analytics
Strong analytical thinking and problem-solving skills
Excellent communication skills, able to convey insights to technical and non-technical audiences
Collaborative mindset, experience working in cross-functional teams
Nice to have:
Experience with other BI tools (e.g., Tableau, Looker)
Familiarity with cloud platforms (Azure, AWS, GCP) for analytics
Knowledge of ETL processes and working with data engineers to integrate pipelines
Experience in governance, documentation, and ensuring data quality across analytics assets