As a Data Visualization & Data Engineer , you will bridge the gap between complex data engineering and strategic business intelligence. You are responsible for designing, developing, and maintaining high-performance Power BI solutions that turn raw data into actionable stories. Working closely with Lead Engineers and Architects, you will leverage the Azure data stack to ensure that the data powering your visualizations is accurate, scalable, and optimized for end-user performance.

Your focus will be on the end-to-end journey of data—from ingestion to the final dashboard.

Design and build interactive, visually compelling Power BI reports and dashboards that adhere to UI/UX best practices and branding standards.

Advanced DAX & Power Query: Author complex DAX (Data Analysis Expressions) for sophisticated business logic and use Power Query (M) to perform advanced data shaping and cleaning.

Semantic Data Modeling: Performance Optimization: Tune Power BI report performance through effective data connectivity (Import vs. Data Pipeline Collaboration: Work with Data Engineers to ensure the Medallion Architecture (Bronze/Silver/Gold) is optimized for BI consumption, occasionally writing PySpark or SQL to refine Gold-layer tables.

Data Governance & Security: Implement Row-Level Security (RLS) and manage workspace permissions within the Power BI Service and Unity Catalog to ensure data privacy.

Automated Testing & DevOps: Participate in the full CI/CD lifecycle using Azure DevOps , implementing version control for .pbix files (using Power BI Projects)



and automating deployment schedules.

What Experience You Need

Visual Engineering Experience: 3–6 years of hands-on experience in BI development, with at least 3 years focused on Power BI.

Azure BI Ecosystem: 4+ years working within Azure (Azure SQL, Synapse, or Databricks) and the Power BI Service (Workspaces, Gateways, Capacities).

Data Transformation: 3+ years of experience with Power Query and SQL for data preparation.

Deep understanding of SQL window functions, joins, and execution plans to validate and troubleshoot the data underlying your reports.

Modeling Foundations: Proven expertise in Dimensional Modeling (SCD types, Fact/Dimension tables) and architecting scalable Power BI datasets.

Education/Certifications: Bachelor's degree in CS, Data Analytics, or a related field.

Microsoft Certified: Power BI Data Analyst Associate (PL-300) is highly preferred.

Azure Data Engineer Associate (DP-203) is a significant plus.

Experience embedding Python or R scripts within Power BI for advanced statistical modeling or custom visuals.

Paginated Reports: Proficiency in Power BI Report Builder for pixel-perfect, operational reporting.

Experience using Databricks SQL and Delta Sharing as high-performance data sources for Power BI.

Embedded Analytics: Knowledge of Power BI Embedded for integrating dashboards into custom web applications.

Data Storytelling: Infrastructure as Code (IaC): Familiarity with using Terraform or specialized tools to automate the provisioning of Power BI workspaces and capacities.

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