Senior Power BI Data Architect - Hybrid

Kruxanalytics

Salt Lake City (UT)

Hybrid

USD 87,000 - 130,000

Full time

14 days+

Application generator

Don’t send a generic resume — generate a resume and cover letter tailored to this exact role.

Get past ATS filters

Benefits offered by this job

Hybrid work schedule

Job summary

Krux is seeking a Data Architect to join our team in a hybrid work environment. You will design, develop, and maintain enterprise-scale Power BI semantic models and architect scalable data models to support multi-tenant analytics.

You will lead governance, optimization, and capacity planning while collaborating with ETL and data pipeline improvements. You will bring 10+ years in data analytics, strong Power BI expertise, and familiarity with Azure cloud data services.

Qualifications

Bachelor’s degree in Computer Science, Technology, Engineering, or related field.
10+ years of experience as a data analytics developer or engineer.
Experience developing data architecture solutions using Tabular Editor is highly desirable.
Experience with databases for high performance, multi-tenant web applications is necessary.
Familiarity with Azure cloud data services.
Experience with dev tools including Git, Azure, DevOps, Visual Studio, Jira.
Understanding of modern data development technologies (data engineering, pipeline, ETL).
Strong attention to detail, critical thinking, and problem-solving skills.

Responsibilities

Design, develop and maintain enterprise-scale Power BI semantic models (tabular).
Architect scalable and high-performance data models to support multi-tenant SaaS analytics.
Define best practices for dataset design, governance, and lifecycle management.
Optimize model performance, DAX calculations, aggregations and storage strategies.
Manage and enhance Power BI service environments (workspaces, deployment pipelines, security).
Monitor and improve analytical database performance in cloud environments.
Conduct model tuning and capacity optimization to support growth and usage scaling.
Evaluate and enhance current analytics platform architecture.
Partner with teammates for ETL and data pipeline improvements.
Provide technical guidance on semantic layer design and analytics best practices.
Support cross-functional stakeholders with scalable reporting architecture.
Assist in high-priority analytics platform issues.