We are seeking a Power BI Architect with deep hands on expertise in designing and delivering enterprise scale analytics solutions on Google Cloud Platform (GCP). The ideal candidate will be responsible for architecting, developing, and governing Power BI semantic models and reports on top of a modern GCP based data and semantic layer.
This role requires strong collaboration with a focus on performance, scalability, security, and business adoption.
Key Responsibilities
Architecture & Design
Lead the architecture and design of Power BI semantic models aligned to enterprise data standards. Define best practices for Power BI datasets, dataflows, and semantic layers built on GCP data platforms.
Architect reusable, scalable, and governed enterprise BI models to support self service analytics. Ensure semantic layer alignment with curated data models (CDM / UDM style models).
Power BI Development (Hands On)
Design, build, and optimize Power BI reports, dashboards, and datasets for performance and usability. Implement complex DAX calculations, KPIs, and measures to support advanced analytics use cases.
Develop certified and shared datasets to enable organization wide analytics. Optimize report performance using modeling techniques, aggregation tables, and query folding.
GCP & Semantic Layer Integration
Build Power BI solutions on top of GCP data sources, including:
BigQuery, Curated / semantic datasets, Feature stores or materialized views
Design semantic models that abstract complexity from underlying GCP data platforms.
Required Skills & Experience
Experience
8–12 years of overall experience in BI, analytics, or data engineering roles.
5+ years of strong, hands on experience with Power BI (Power BI Service, Desktop, DAX). Proven experience architecting enterprise semantic layers and BI platforms.
Technical Skills
Advanced expertise in:
Power BI semantic modeling, DAX optimization and complex calculations, Power BI performance tuning
Strong experience integrating Power BI with GCP, especially:
BigQuery, Curated datasets / views
Solid understanding of: Dimensional modeling (Star/Snowflake), Semantic layer concepts, Data warehousing best practices
Cloud & Data Skills
Hands on experience working in Google Cloud Platform (GCP). Familiarity with cloud native analytics and modern data platforms. Experience working alongside data engineering pipelines (ELT/ETL).