Strong SQL & Reporting analyst having strong expertise in Extract, Transform, Load (ETL) processes, SQL querying, and reporting, with hands-on experience in an AWS cloud environment. Key Responsibilities Design, develop, and maintain scalable ETL workflows to extract data from various sources, transform it based on business requirements, and load it into data warehouses or databases. SQL Querying: Write complex SQL queries to extract, manipulate, and analyze data for reporting and ad-hoc business requests. Reporting: Create, optimize, and automate reports and dashboards using Power BI, or AWS QuickSight to deliver actionable insights to stakeholders. AWS Environment: Understanding of how to leverage AWS services (e.g., S3, Redshift, Glue, Lambda) to store, process, and manage data efficiently in a cloud-based ecosystem. Data Integrity: Ensure data accuracy, consistency, and quality throughout the ETL and reporting processes by implementing validation checks and troubleshooting issues. Collaboration: Work closely with data engineers, business analysts, and stakeholders to understand data needs and deliver tailored solutions. Optimization: Monitor and optimize ETL processes and queries for performance and scalability. Documentation: Maintain clear documentation of ETL processes, data models, and reporting logic for future reference and team knowledge sharing. Soft Skills Communication: Ability to communicate effectively with non-technical stakeholders to understand requirements. Team Collaboration: Experience working in teams using Agile or Scrum methodologies. Technical Skills Experience: 3+ years of experience in ETL development, data analysis, or a similar role. SQL Skills: Advanced proficiency in writing and optimizing complex SQL queries (e.g., joins, subqueries, window functions). AWS Expertise: Hands-on experience with AWS services such as S3, Redshift, Glue, Lambda, or Athena for data storage and processing. Reporting Tools: Proficiency in visualizations and dashboards using Power BI Programming: Familiarity with scripting languages like Python or Bash for automation and data manipulation is a plus. Data Concepts: Strong understanding of data warehousing, data modeling, and ETL best practices. Problem-Solving: Ability to troubleshoot data issues and optimize processes efficiently. Communication: Excellent verbal and written communication skills to collaborate with technical and non-technical stakeholders.