Power BI Engineer / Developer

Data Engineering & Analytics Design, develop, and maintain scalable ETL/ELT pipelines integrating structured and semi-structured data from databases, APIs, files, cloud platforms, and enterprise applications. Collaboration & Delivery Gather business requirements and collaborate with stakeholders, analysts, data engineers, and technology teams to deliver reliable, governed analytics solutions.

Job Title: Power BI Engineer / Developer
Location: Phoenix, AZ, (Onsite)
Duration: 6 Months


Salary Range: $40.00 - $42.00/Hour on W2 (Without Benefits).
Applicants must be willing to work on W2.

Required Experience:

• Overall Experience Required is 5 – 8 years.
• Must Have 7+ years of hands-on experience in Microsoft Power BI.

Power BI & Business Intelligence:

• Design, develop, and maintain enterprise-grade Power BI dashboards, reports, and semantic models.
• Build interactive visualizations that translate complex datasets into actionable business insights.
• Develop advanced DAX calculations, business logic, and Power Query / M transformations for data cleansing and preparation.
• Design and optimize semantic models, relationships, star/snowflake schemas, dimensional models, and reusable semantic layers.
• Implement Row-Level Security (RLS), Import/DirectQuery/composite models, incremental refresh, and data gateways.
• Establish reusable reporting standards, templates, KPI definitions, and visualization best practices.
• Manage deployments across development, testing, and production environments; troubleshoot refresh, gateway, semantic-model, and report-performance issues.
• Use Power BI REST APIs, Tabular Editor, and DAX Studio as needed. Microsoft Fabric experience is highly desirable.

Data Engineering & Analytics

• Design, develop, and maintain scalable ETL/ELT pipelines integrating structured and semi-structured data from databases, APIs, files, cloud platforms, and enterprise applications.
• Develop and optimize SQL queries, stored procedures, views, and transformation logic.
• Build and maintain data warehouses, data lakes, and lakehouse solutions using dimensional modeling and appropriate data architectures.
• Implement data cleansing, transformation, validation, reconciliation, and data-quality processes.
• Develop reusable data pipelines and frameworks using Python, PySpark, SQL, and cloud-native services.
• Implement pipeline monitoring, logging, error handling, alerting, and operational support.
• Optimize data processing workloads for performance, reliability, scalability, and cost efficiency.
• Support metadata management, data lineage, governance, and data-quality practices.

DevOps, Governance & Quality:

• Apply Git-based version control and CI/CD practices using Azure DevOps, GitHub, and Power BI deployment pipelines.
• Implement data security, role-based access controls, metadata management, lineage, and governance standards.
• Diagnose performance bottlenecks across SQL queries, data pipelines, semantic models, and Power BI reports.
• Maintain technical documentation covering architectures, data models, business rules, and operational processes.

Collaboration & Delivery

• Gather business requirements and collaborate with stakeholders, analysts, data engineers, and technology teams to deliver reliable, governed analytics solutions.
• Translate business needs into scalable technical designs and actionable reporting solutions.
• Deliver end-to-end analytics products, from source-data ingestion and transformation through semantic modeling and executive-ready Power BI reporting.
• Work effectively in Agile and cross-functional environments, communicating technical concepts clearly to technical and non-technical stakeholders.

Preferred Technologies:

• Microsoft Azure, Azure Data Factory, Azure Synapse Analytics, and Azure Databricks.
• Microsoft Fabric Data Factory, Fabric Data Engineering, OneLake, Lakehouse, and Delta Lake.
• SQL Server, Azure SQL, and Snowflake.

Key Competencies

• Stakeholder management and requirements gathering.
• Analytical thinking and problem-solving.
• Cross-functional collaboration and communication.
• Agile delivery and attention to detail.
• Data accuracy, security, governance, scalability, and maintainability.