Business Intelligence Engineer Amazon QuickSight / AWS Analytics
Key Responsibilities
1. QuickSight Development & Dashboard Engineering
Design, develop, and maintain interactive dashboards, datasets, and visualizations in Amazon QuickSight.
Build high-performance dashboards optimized for large datasets and fast refresh times.
Implement row-level security (RLS) and governance controls for business users.
Create standardized QuickSight templates and dashboard frameworks that can be reused across teams.
Design and maintain semantic layers and curated datasets for reporting.
Optimize dashboards to reduce SPICE usage, refresh costs, and compute consumption.
2. Self-Service BI Enablement
Work directly with business users and analysts to enable self-service reporting capabilities.
Provide guidance on best practices for dashboard design and data consumption.
Create reusable data models, templates, and reporting accelerators.
Develop training materials and documentation for business teams to build their own dashboards.
Conduct workshops and enablement sessions for business users on QuickSight usage.
3. Data Modeling & Dataset Engineering
Design and maintain optimized datasets and data models for BI reporting.
Build reusable data flows and data pipelines that serve multiple reporting use cases.
Work with engineering teams to integrate data from sources such as:
AWS Redshift
S3
Athena
RDS
Glue Data Catalog
Ensure datasets follow governance, quality, and consistency standards.
4. Reporting Frameworks & Reusable Components
Create reusable reporting templates, dataset templates, and QuickSight themes.
Build standardized KPIs, calculated fields, and metric definitions.
Design modular reporting components that can be used across multiple dashboards.
Implement parameterized dashboards and reusable visual components.
5. Performance Optimization & Cost Management
Identify opportunities to reduce compute costs associated with reporting workloads.
Optimize use of SPICE vs direct query based on performance and cost requirements.
Monitor and tune query performance across Athena, Redshift, and other data sources.
Implement efficient refresh schedules and dataset management strategies.
Provide recommendations for cost-efficient reporting architectures on AWS.
6. Collaboration with Business & Data Teams
Partner with product owners, business analysts, and leadership teams to understand reporting requirements.
Translate business needs into scalable BI solutions.
Work with data engineering teams to ensure required datasets are available and optimized.
Participate in requirements gathering and reporting roadmap planning.
7. Governance, Documentation & Standards
Establish BI standards and governance for QuickSight dashboards.
Maintain documentation for:
datasets
metrics
dashboard logic
reporting frameworks
Ensure adherence to data security and access policies.
Implement naming conventions and versioning for dashboards and datasets.
Required Qualifications
8+ years of experience in Business Intelligence, Analytics Engineering, or Data Visualization.
Strong hands-on experience with Amazon QuickSight.
Experience designing interactive dashboards and enterprise reporting solutions.
Solid knowledge of SQL and data modeling.
Experience working with AWS analytics services such as:
Athena
Redshift
S3
Glue
Experience enabling self-service analytics for business users.
Strong understanding of data visualization best practices.
Experience optimizing reporting performance and cost efficiency.
Preferred Qualifications
Experience building QuickSight templates, themes, and reusable datasets.
Experience with BI governance and semantic layer design.
Familiarity with data pipelines and ETL frameworks.
Knowledge of AWS cost optimization strategies.
Experience supporting large-scale enterprise reporting environments.
Experience with other BI tools such as Tableau, Power BI, or Looker.
Key Skills
Amazon QuickSight
SQL & Data Modeling
AWS Analytics Stack
Dashboard Design
BI Architecture
Self-Service Analytics Enablement
Performance Optimization
Cost Optimization
Stakeholder Communication
Deliverables / Expected Outcomes
Standardized QuickSight reporting templates
Reusable datasets and semantic reporting layers
Improved self-service BI adoption across business teams
Reduced compute and reporting infrastructure costs
Scalable dashboard frameworks and governance standards
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