Key Responsibilities Analytics & Reporting: Design, develop, and maintain intuitive, interactive dashboards and reports using AWS QuickSight. Data Connectivity: Integrate and manage datasets from multiple sources such as Snowflake, Amazon S3, RDS, SQL Server, and external APIs. Stakeholder Engagement: Collaborate closely with business stakeholders and data analysts to collect requirements and convert them into meaningful insights. Data Modeling & Querying: Build efficient data models, define relationships, and develop SQL queries to support data transformation and analysis. Optimization: Improve dashboard responsiveness, query efficiency, and overall data access performance. Data Governance: Maintain high standards of data accuracy, consistency, and reliability across all visualizations. Security Management: Configure and maintain access controls, including IAM policies and row-level security. Process Automation: Automate repetitive tasks using Python or Bash, with optional use of AWS Lambda. User Enablement: Deliver ongoing support and conduct training sessions for end users. Knowledge Sharing: Prepare and maintain documentation covering data models, reporting logic, and operational processes. Continuous Improvement: Keep up to date with new AWS QuickSight capabilities and industry best practices. Required Skills & Experience Bachelor’s degree in Computer Science, Information Technology, or a comparable discipline. Demonstrated advanced proficiency in AWS QuickSight, including SPICE, visual components, filters, and actions. Solid knowledge of data warehousing principles, data modeling techniques, and ETL processes. Strong command of SQL for data analysis and transformation. Hands-on experience with AWS data services (S3, Glue, RDS), as well as DBT and Snowflake. Strong analytical mindset with excellent problem-solving abilities. Clear and effective written and verbal communication skills. Ability to work autonomously while also contributing effectively within a team environment.