Lead BI Engineer (Contract-to-Hire)

Soltech•Alpharetta, GA

2d•Onsite

About The Position

Our client is seeking an experienced Lead Business Intelligence (BI) Engineer to join their Data & Analytics team in a full-time capacity. This role combines two key responsibilities: Primary: Own the ongoing maintenance and optimization of enterprise Power BI semantic models, including TMDL/Model.bim, DAX development, relationships, row-level security (RLS), and workspace governance. Secondary: Contribute to the continued development of a Snowflake data warehouse by extending GOLD-layer dimensional models (facts and dimensions) that support enterprise analytics and reporting initiatives. This is an AI-first engineering role where modern AI-assisted development practices are central to the team's workflow. The successful candidate will use Claude Code as the primary development environment, leveraging an established multi-repository framework that includes project-specific context, reusable development skills, AI-assisted code orchestration, and integrated tools for Snowflake, SQL Server, and Jira. Candidates should be comfortable working within AI-assisted development environments and taking full ownership of the quality, accuracy, and maintainability of AI-generated solutions.

Requirements

7+ years of Business Intelligence experience.
3+ years of hands-on experience developing and maintaining Power BI semantic models.
Advanced expertise with: Power BI DAX, Power Query (M), TMDL/Model.bim, Tabular Editor
Strong SQL development skills.
Experience designing and maintaining dimensional data models within a cloud data warehouse, preferably Snowflake.
Deep understanding of Kimball dimensional modeling methodologies.
Hands-on experience using Claude Code or comparable AI-powered coding platforms (such as Codex CLI or GitHub Copilot CLI) in daily software development workflows.
Ability to evaluate, explain, and take ownership of AI-assisted development output.
Experience implementing Row-Level Security (RLS) and administering Power BI workspaces.
Experience preparing semantic models for Power BI Copilot through optimized metadata, relationships, and natural language capabilities.
Experience collaborating with data engineering teams on enterprise data warehouse development.

Nice To Haves

Experience building or extending AI development tooling, including reusable skills, MCP servers, or AI agent configurations.
Experience with GitHub Actions, CI/CD pipelines, and GitHub-based code review processes.
Exposure to SSRS or migrations from legacy SSAS environments.
Experience with Azure Data Factory or comparable ELT/orchestration platforms.
Background supporting financial services, nonprofit, foundation, or philanthropic organizations.

Responsibilities

Maintain and enhance enterprise Power BI semantic models using TMDL/Model.bim and Tabular Editor.
Develop and optimize DAX measures, calculated columns, Power Query (M) transformations, and semantic model performance.
Design, implement, and manage Row-Level Security (RLS).
Administer Power BI workspaces, including governance, permissions, lifecycle management, and naming standards.
Ensure semantic models remain aligned with upstream Snowflake GOLD-layer changes.
Provide guidance, documentation, troubleshooting, and support to report developers and business users.
Optimize semantic models for Power BI Copilot, including metadata, naming conventions, relationships, descriptions, synonyms, and Q&A capabilities to improve natural language interactions.
Extend and maintain GOLD-layer dimensional models, including fact and dimension tables, to support evolving business requirements.
Apply Kimball dimensional modeling best practices throughout the analytics ecosystem.
Collaborate closely with the data engineering team to implement well-defined warehouse enhancements.
Validate end-to-end data quality from Snowflake through semantic models and downstream reporting solutions.
Utilize Claude Code as the primary development environment for Power BI, DAX, semantic modeling, and Snowflake development.
Leverage existing AI workflows, reusable skills, validation scripts, and multi-repository orchestration to improve development efficiency.
Expand and maintain the team's reusable AI skill library and development standards as best practices evolve.
Utilize integrated tools for Snowflake, SQL Server, and Jira within the AI development environment.
Review, validate, and take full ownership of AI-assisted code before deployment.
Collaborate with cross-functional teams on multi-repository changes and technical impact assessments.
Mentor team members on Business Intelligence best practices as well as AI-assisted development workflows.