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Google BigQuery Data Analyst
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Job Description
Job Description
A Google BigQuery Data Analyst role typically involves developing and executing complex SQL queries to analyze large datasets in BigQuery, performing in-depth data analysis to identify trends and patterns, and creating data visualizations to communicate findings to stakeholders. Responsibilities:
Data Analysis:
Experience working with large-scale datasets and complex data structures.
Experience working with data migrated from SAP applications with underlying Oracle databases.
Develop and execute complex SQL queries to extract, transform, and analyze large datasets in BigQuery.
Conduct in-depth data analysis to identify patterns, trends, and anomalies.
Create visualizations (e.g., dashboards, charts) to communicate findings effectively to stakeholders.
Proficiency in data visualization tools (e.g., Looker). Data Modeling:
Strong understanding of data warehousing and data modeling concepts.
Design and implement data models that optimize query performance and data accessibility.
Collaborate with data engineers to ensure data quality and consistency.
Stakeholder Communication:
Clearly communicate findings and recommendations to both technical and non-technical audiences.
Build strong relationships with stakeholders to understand their needs and priorities
Candidate requirements:
3+ years leveraging BigQuery to drive data-driven insights and inform strategic decision-making
Expertise in writing and optimizing complex SQL queries.
Strong analytical skills to identify trends and patterns in large datasets.
Deep familiarity with Google BigQuery's functions and data processing capabilities.
Ability to design efficient data models for performance optimization.
Proficiency with tools like Looker for creating dashboards and visual reports.
Effectively present findings to both technical and non-technical stakeholders.
Hybrid position based Chicago Area.
Data Analysis:
Experience working with large-scale datasets and complex data structures.
Experience working with data migrated from SAP applications with underlying Oracle databases.
Develop and execute complex SQL queries to extract, transform, and analyze large datasets in BigQuery.
Conduct in-depth data analysis to identify patterns, trends, and anomalies.
Create visualizations (e.g., dashboards, charts) to communicate findings effectively to stakeholders.
Proficiency in data visualization tools (e.g., Looker). Data Modeling:
Strong understanding of data warehousing and data modeling concepts.
Design and implement data models that optimize query performance and data accessibility.
Collaborate with data engineers to ensure data quality and consistency.
Stakeholder Communication:
Clearly communicate findings and recommendations to both technical and non-technical audiences.
Build strong relationships with stakeholders to understand their needs and priorities
Candidate requirements:
3+ years leveraging BigQuery to drive data-driven insights and inform strategic decision-making
Expertise in writing and optimizing complex SQL queries.
Strong analytical skills to identify trends and patterns in large datasets.
Deep familiarity with Google BigQuery's functions and data processing capabilities.
Ability to design efficient data models for performance optimization.
Proficiency with tools like Looker for creating dashboards and visual reports.
Effectively present findings to both technical and non-technical stakeholders.
Hybrid position based Chicago Area.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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