- Design, develop, and maintain data transformation pipelines using dbt (Core/Cloud).
- Build scalable and reusable data models following Kimball/Data Vault methodologies.
- Develop and optimize complex SQL queries for large-scale datasets.
- Create and manage incremental models, snapshots, seeds, tests, and macros in dbt.
- Implement data quality checks, validation frameworks, and monitoring processes.
- Collaborate with Data Architects, Data Analysts, Business stakeholders, and engineering teams to gather requirements.
- Develop and maintain ELT/ETL workflows using tools such as Airflow, Azure Data Factory, or similar orchestration platforms.
- Optimize data warehouse performance and ensure adherence to best practices.
- Perform code reviews, mentor junior developers, and establish development standards.
- Manage CI/CD deployment processes for dbt projects.
- Troubleshoot production issues and ensure data reliability and availability.
- Document data models, lineage, and technical processes.