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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expert-level mastery of Google BigQuery and Dataform for developing and optimizing data transformation pipelines. Proficient in applying Kimball methodology to design dimensional data warehouses and ensuring data quality for business reporting.
Highest-signal resume keywords
Google BigQueryDataformDimensional Data WarehousingAdvanced SQLData Quality Assurance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data TransformationExploratory Data AnalysisPerformance TuningCost OptimizationData ModelingSQL QueryingData Warehousing SchemasData ProfilingBigQuery MLPython
Tools & Technologies
LookerTableauPower BIGit
Industry Keywords
Kimball MethodologyStar SchemaSnowflake SchemaData MartsBusiness Intelligence
Tech Stack
Tools & technologiesBigQueryPythonSnowflakeSQLTableau
About the role
Key responsibilities & impact- Lead the development, maintenance, and optimization of the entire data transformation lifecycle using Dataform
- Build and manage scalable, well-documented, and tested data transformation pipelines for business reporting
- Conduct Exploratory Data Analysis on new and existing datasets to identify quality issues, understand data structures, and unlock business value
- Write performant BigQuery SQL for complex queries, aggregations, and data manipulation, focusing on cost and speed optimization
- Implement data quality and validation checks to ensure accuracy and trust in reporting datasets
- Own the transformation and modeling layers of a new data warehouse project
- Apply Kimball methodology principles to create clean, reliable, and performant dimensional data models
Requirements
What you’ll need- Expert-level mastery of Google BigQuery, including Dataform
- Demonstrable, in-depth experience designing and building dimensional data warehouses using Kimball's principles
- Mastery of Dataform for developing, testing, and deploying complex SQL-based data transformation workflows in a production environment
- Demonstrable mastery of advanced SQL, including window functions, CTEs, and complex joins
- Deep, hands-on experience with BigQuery, including performance tuning, cost optimization, and partitioning/clustering
- Strong, practical knowledge of data warehousing schemas: Star Schema, Snowflake Schema, and Data Marts
- Ability to analyze and profile datasets to derive insights and assess quality
- Experience preparing data for BI tools like Looker, Tableau, or Power BI
- Proficiency in using Git for managing SQL and Dataform code
- Experience with BigQuery ML is a significant plus
- 4 years of experience required
- Required skills: Google BigQuery, Python, Gemini Enterprise, and Artificial Intelligence (AI)