This project is a distributed, cloud-based aviation software platform built to manage real-time operational data across: * flight planning and dispatch * crew scheduling * aircraft maintenance * financial and operational workflows
The platform processes large, multi-tenant datasets and supports data-driven decision-making for operational and management teams.
Your Role
You will be responsible for building, maintaining, and continuously improving Amazon QuickSight dashboards based on aviation-related data. The role focuses on transforming large, complex datasets into clear, actionable insights for multiple stakeholders.
Key Responsibilities * Design, develop, and maintain interactive dashboards and datasets in Amazon QuickSight. * Write and optimize complex SQL queries (including CTEs and window functions) to support analytical use cases. * Perform data analysis using Python (pandas; boto3 is a plus). * Ensure high standards of data quality, data governance, and multi-tenant data isolation. * Summarize analytical findings and translate them into intuitive, insightful visualizations. * Collaborate closely with product, engineering, sales, and management teams to support data-driven decision-making. * Contribute to and improve ETL processes and data pipelines.
Required Qualifications * University degree in Computer Science, Data Science, Statistics, or equivalent practical experience. * Strong analytical mindset with proven experience working with large datasets. * Advanced proficiency in SQL and solid experience with Python for data analysis. * Hands-on experience with Amazon QuickSight (or Quick Suite), ideally 2+ years, including: * Dashboards and datasets * Calculated fields * Row-Level Security (RLS) * (Bonus) Paginated Reports * Excellent written and spoken English, with the ability to clearly explain complex concepts. * Structured, detail-oriented, and reliable — you consistently deliver and close tasks. * Curious, proactive, and motivated to continuously learn new tools and approaches.
Nice to Have * Experience with ETL processes. * Experience working with cloud data warehouses such as Amazon Redshift and data lakes (S3 or similar). * Portfolio, examples, or case studies demonstrating previous dashboards or analytical work.
