We are looking for a skilled Data Analytics Engineer with deep expertise in Power BI to join our team in Ankeny, Iowa. In this role, you will design, optimize, and manage semantic data models while ensuring the seamless performance of business intelligence tools. Your contributions will help drive data-driven decision-making across the organization.<br><br>Responsibilities:<br>• Design and implement semantic data models, including dimensional modeling and star schemas, to support business intelligence needs.<br>• Develop and optimize Power BI reports and dashboards, ensuring high performance and efficient query execution.<br>• Utilize Power Query (M) to transform and manipulate data for reporting purposes.<br>• Configure and enforce row-level security within Power BI to safeguard sensitive data.<br>• Conduct performance tuning for Power BI, including query plan optimization and refresh strategies.<br>• Collaborate with stakeholders to understand analytical requirements and translate them into actionable insights.<br>• Leverage tools such as Tabular Editor and deployment pipelines (Azure DevOps, GitHub) to streamline BI asset management.<br>• Work with cloud-based data platforms, including Databricks, Snowflake, or BigQuery, to support lakehouse architectures.<br>• Maintain adherence to enterprise BI governance practices and ensure scalable solutions for large datasets.<br>• Implement CI/CD patterns to manage semantic models and facilitate environment promotions.

• Minimum of 3-5 years of experience in analytics engineering, BI engineering, or semantic data modeling.<br>• Advanced expertise in Power BI, including semantic model design and performance optimization.<br>• Strong knowledge of dimensional modeling concepts such as facts, dimensions, and star schemas.<br>• Proficiency in Power Query (M) and row-level security configurations.<br>• Familiarity with tools such as Tabular Editor and deployment pipelines like Azure DevOps or GitHub.<br>• Experience working with cloud data platforms, such as Databricks, Snowflake, or BigQuery.<br>• Understanding of CI/CD practices for managing semantic models and BI assets.<br>• Exposure to enterprise BI governance practices and handling large datasets.

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