> Markdown version of [/jobs/ext/4227420-google-cloud-platform-data-engineer](https://www.wearedevelopers.com/jobs/ext/4227420-google-cloud-platform-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Google Cloud Platform Data Engineer - **Company:** Stefanini - **Location:** United States - **Contract:** Permanent contract - **Skills:** Query Performance, Airflow, BigQuery, Continuous Integration, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Dimensional Modeling, Data Flow Control, Python (Programming Language), Power BI, Standard Sql, SQL Databases, Google Cloud, Delivery Pipeline, Snowflake, Powerquery, Data Layers, Information Technology, Semantic Modeling, Software Version Control, Data Pipelines - **Published:** October 8, 2026 - **Apply:** https://www.dice.com/job-detail/7cb9e7ae-8109-4df7-adc2-ea82fd9deeaf ## About the Role We are seeking an experienced Data Engineer with strong expertise in Power BI semantic modeling and Google Cloud BigQuery. Experience in data engineering and business intelligence, with a proven track record of building and optimizing enterprise-scale Power BI models, reports, and dashboards. In this role, you will lead analytics initiatives, establish best practices for querying and transforming large BigQuery datasets, and partner with business and technical stakeholders to deliver high-performance, actionable insights., Experience Required10+ years of Business Intelligence experience, with a strong focus on Power BI and enterprise reporting.Advanced Power BI skills, including semantic modeling, DAX, Power Query (M), schema design, composite models, and paginated reports.Strong SQL skills and hands-on experience optimizing queries in Google BigQuery.Solid understanding of data engineering, data warehousing, ETL/ELT, dimensional modeling, and data pipelines.Experience with Power BI Service administration, security, gateways, publishing, and refresh optimization.Experience gathering business requirements, documenting reporting logic, and validating results with stakeholders.Excellent analytical, problem-solving, and communication skills, with the ability to work independently and collaboratively in an agile environment. Experience Required7+ years of Data Engineering work experience Education RequiredBachelor's degree in Computer Science, Information Technology, or a related field. ## Description Power BI Semantic ModelingDesign and maintain enterprise semantic models using star and snowflake schemas.Select appropriate storage modes, including Import, DirectQuery, Dual, Direct Lake, and composite models.Develop reusable, well-documented DAX measures, calculation groups, M-query transformations, role-playing dimensions, incremental refresh, and aggregation tables.Promote certified shared datasets, thin reports, consistent business definitions, and model documentation standards. BigQuery and Data EngineeringDevelop and optimize complex BigQuery SQL, including CTEs, window functions, and large-scale joins.Apply best practices for partitioning, clustering, views, materialized views, query performance, and cost management.Partner with data engineers on ETL/ELT pipelines, curated data layers, and dimensional models.Build reporting-ready BigQuery tables or views, with heavy transformations performed upstream where appropriate.Implement data validation, reconciliation, and quality rules.Understand orchestration and pipeline concepts; experience with Dataflow, Cloud Composer/Airflow, or Python is a plus. Performance, Administration, and GovernanceOptimize reports and models using tools such as Performance Analyzer, DAX Studio, Tabular Editor, and VertiPaq Analyzer.Improve refresh performance through query folding, incremental refresh, and efficient partitioning.Manage Power BI Service workspaces, deployment pipelines, gateways, refresh schedules, and capacity.Implement row-level and object-level security and follow governance, access, and compliance standards.Support CI/CD and version control for BI assets, and monitor usage, refresh failures, and capacity. Business Engagement and RequirementsPartner with business stakeholders and end users to understand reporting needs, pain points, and the decisions reports must support.Capture report logic, including data grain, filters, exclusions, defaults, hierarchies, drill paths, time intelligence, and the treatment of null, negative, cancelled, or reversed records.Translate requirements into functional and technical specifications, mappings, and logical data models.Prioritize the backlog, agree on milestones and acceptance criteria, and lead UAT and reconciliation with source or legacy reports.Provide user training, documentation, and ongoing support.