AWS QuickSight BI Developer
New
Based in United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 5–8 years
- Required Skills
- SQLBusiness IntelligenceData visualizationData modeling
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Business, or related field, or equivalent experience.
- 5–8 years of experience in business intelligence, analytics engineering, reporting, or data visualization.
- Hands-on experience designing and developing dashboards and reporting solutions using Amazon QuickSight.
- Strong SQL skills and experience with relational and analytical data modeling.
- Experience working with AWS analytics services including Athena, Redshift, S3, RDS, and Glue.
- Proven ability to create reusable datasets, KPI frameworks, calculated fields, and dashboard templates.
- Knowledge of dashboard optimization, performance tuning, and analytics cost-management.
- Experience using AI-assisted development tools such as Amazon Q, GitHub Copilot, or ChatGPT Enterprise.
- Strong communication skills for explaining technical concepts to non-technical stakeholders.
- Ability to obtain and maintain public trust access for federal information systems.
Responsibilities
- Design, develop, enhance, and maintain interactive dashboards, analyses, visualizations, and datasets using Amazon QuickSight.
- Build high-performance reporting solutions optimized for large data volumes, usability, refresh efficiency, and operational reliability.
- Develop curated datasets, semantic reporting layers, and reusable data models that support enterprise analytics requirements.
- Create standardized dashboard templates, KPI definitions, calculated fields, QuickSight themes, and modular reporting components.
- Implement data governance practices, including row-level security, role-based access controls, and permissions management.
- Collaborate with business stakeholders, engineers, and product owners to translate requirements into scalable BI solutions.
- Enable self-service analytics by developing documentation, training materials, and reusable frameworks.
- Integrate and optimize data sources across AWS services such as Redshift, Athena, S3, RDS, and Glue Data Catalog.
- Monitor and improve reporting performance, reliability, and cloud cost efficiency.
- Leverage AI-assisted development tools to improve dashboard creation and automation.
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