Data Modeler

• Build end-to-end automated pipeline workflows for complex aviation data ingestion, processing, and transformation
• Develop reusable scripts and models for ingestion, orchestration, and transformations using Python, SQL, dbt, and R (where applicable), setting the foundation for scalable data workflows
• Create and maintain detailed Source-to-Target (S2T) mapping diagrams, clearly documenting data flow, transformation logic, business rules, and data quality checks to guide ETL/ELT development
• Develop a Data Quality Module (monitoring ingestion, transformation, and publication) and a Data Stewardship Module (supporting human-in-the-loop validation/correction) using dbt and Streamlit
• Adhere to modern CI/CD practices and ensure thorough documentation and knowledge transfer to internal staff for sustainable operations

• 7+ years in Data Engineering, Architecture, or Analytics Consulting, preferably within complex or regulated industries like Aviation
• Proficiency in Python, SQL, and dbt for sophisticated ETL/ELT development
• Strong experience with modern cloud data warehousing, specifically Snowflake
• Experience with AWS services and data orchestration tools
• Familiarity with R for statistical transformations is a plus
• Strong understanding of data modeling principles and hands-on experience designing Source-to-Target mapping
• Proven experience designing and implementing robust data quality frameworks and validation checks
• Excellent communication and documentation skills are essential for knowledge transfer and stakeholder collaboration

Familiarity with R for statistical transformations is a plus