We are looking for a Senior Power BI Engineer to join the development of a next-generation AI-powered analytics platform built for community banks and credit unions in the US.
The platform enables business users to ask complex financial questions in plain English and receive instant answers, visualizations, and actionable insights. To achieve this, we combine Power BI, semantic modeling, modern Azure data architecture, and Large Language Models (LLMs).
This is a highly technical role at the intersection of Business Intelligence, Data Modeling, and AI.
Location: Remote (Europe)
Employment: Full-time
Schedule: Some overlap with US time zones is expected.
What Will You Do:
Design, develop, and maintain high-performance Power BI data models and reporting layers integrated into a standalone web application.
Build and evolve the Platinum (Semantic) Layer, translating complex banking concepts into governed, metadata-driven data models.
Implement and support Model Context Protocol (MCP) integrations, enabling AI agents to leverage Power BI semantic and visualization capabilities.
Design and enforce data governance, Row-Level Security (RLS), and multi-tenant data isolation strategies.
Optimize reporting performance with a target response time of under 5 seconds.
Collaborate closely with Data Engineers to validate AI-generated SQL queries against automated testing and reporting standards.
Work in an AI-first development environment, leveraging advanced AI tools to accelerate delivery and decision-making.
Who You Are:
4+ years of experience as a Power BI Engineer, BI Developer, or Data Analyst with strong Power BI expertise.
Deep understanding of Power BI Data Modeling, including Star Schema and Kimball dimensional modeling.
Advanced knowledge of DAX and Power Query (M).
Strong T-SQL skills and solid understanding of relational database design.
Experience implementing complex Row-Level Security (RLS), ideally in multi-tenant environments.
Upper-Intermediate English or higher.
Will be a Plus:
Experience with Model Context Protocol (MCP) or Power BI Embedded solutions.
Experience integrating AI/LLM technologies with analytics platforms.
Knowledge of Azure AI Foundry, GPT-based solutions, or AI-assisted analytics.
FinTech or Banking domain experience.
Experience with Azure SQL Database, Azure Data Factory, or Azure Data Lake Storage.
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