Analytics Engineer

About the role

The IT capability at Koch Engineered Solutions (KES) is a vital part of our strategy to enhance business performance through technology. Our team operates with a startup mentality, collaborating with Engineering, Operations, Commercial, and Finance teams to innovate and transform KES work processes.

Responsibilities

• Partner with analysts and business stakeholders to understand data gaps, define metrics, and design robust, scalable analytics solutions
• Design and build dimensional models that are clean, performant, and easy to use
• Create and optimize SQL transformations to convert data into business-friendly and reusable dimensional model objects
• Create and maintain Power BI semantic models that enable clear and efficient self-service analytics
• Develop and maintain enterprise Power BI reports and dashboards with a focus on usability, performance, and consistent business definitions
• Implement and follow professional development practices such as Git-based version control, branching/PR workflows, testing/validation, CI/CD, etc.
• Collaborate with data engineers, architects, and other analytics engineers to align on standards for naming, documentation, data quality, and model governance
• Support adoption by documenting models and metrics, enabling stakeholder training, and improving discoverability
• Troubleshoot data issues with data models and reports and continuously improve reliability and performance

Requirements

• 3+ years in analytics engineering, BI development, or a similar role with significant data modeling responsibilities
• Bachelor’s degree in a quantitative, analytical, or engineering field (e.g., Data Science, Computer Science, Information Systems, Engineering, Mathematics) or equivalent practical experience delivering analytics outcomes
• Strong SQL skills for data transformation
• Demonstrated experience building dimensional data models for BI applications
• Hands-on experience with Power BI semantic model and report development
• Experience with Power Query (M) and understanding of when/how to use it effectively
• Experience using Git in a team environment (branches, PRs, code reviews)
• Strong communication skills and comfort working directly with stakeholders

Qualifications

• Deep knowledge of dimensional modeling best practices and optimization techniques
• Experience with dbt (models, tests, documentation, macros, exposures)
• Experience using Snowflake for data transformation, including developing SQL-based pipelines and reusable model layers
• Familiarity with Microsoft Fabric for data engineering and BI development
• Awareness of Agile SDLC practices
• Experience designing reusable semantic standards for enterprise reporting
• Exposure to data quality and observability practices
• Experience enabling AI-capable models through strong metadata, consistent definitions, curated semantic layers, and documentation
• Experience with Agentic development and workflows