Power Bi + Data Engineer

Power Bi + Data Engineer Location – Washington, D.C (Remote) Duration – Contract / Full time Analytics Engineer – Data Engineering & Power BI We are looking for a hands-on Analytics Engineer who can work across both data engineering and analytics/reporting.

This is not a Power BI-only role. The ideal candidate should be comfortable owning data tasks end-to-end — from understanding source data and building transformation pipelines to creating well-designed datasets and Power BI dashboards.

Key Responsibilities Build, maintain, and enhance data pipelines and transformation workflows using dbt and python DAG in Airflow. Develop clean, reliable, and reusable data models for analytics and reporting.

Work with SQL and data warehouse platforms to investigate data, troubleshoot issues, and implement transformations. Develop and maintain Power BI dashboards, reports, semantic models, and DAX measures.

Translate business requirements into appropriate data models and reporting solutions. Perform data analysis, validation, reconciliation, and data quality checks. Troubleshoot data issues across the pipeline, from source through transformation to reporting.

Take ownership of assigned tasks and independently drive them through development, testing, and completion. Work closely with business, analytics, and engineering teams to deliver production-ready solutions.

AI Forward - Understand how to marry AI tools to enhance productivity on tasks Required Skills Strong SQL and data analysis skills. Strong Python for data pipelines for complex transformations and integrations.

Hands-on experience with dbt and/or modern ELT/data transformation practices. Solid understanding of data modeling, including dimensional modeling, fact/dimension structures, and analytics datasets. Experience working with a modern cloud data warehouse, preferably Snowflake.

Strong working experience with Power BI, including data modeling, DAX, dashboard development, and performance considerations. Ability to understand unfamiliar datasets and identify relationships, data quality issues, and transformation requirements.

Experience debugging and supporting existing data pipelines and analytics solutions. Comfortable working independently in a fast-paced environment and delivering tasks with limited supervision.