Description
Job Summary:
Develop, test, and maintain DBT models and data transformation pipelines, collaborating with analysts and stakeholders to optimize queries and ensure data quality.
Key Highlights:
1. Proficiency in DBT for data modeling and transformation
2. Strong SQL knowledge and experience with Git
3. Hands-on experience with AWS and understanding of ETL/ELT
Description: Required Qualifications:
* Proficiency with DBT (Data Build Tool) for data modeling and transformation.
* Strong SQL knowledge (preferably with experience in Snowflake, BigQuery, Redshift, or similar).
* Experience with version control systems such as Git.
* Familiarity with data warehouse concepts and dimensional modeling.
* Understanding of ETL/ELT processes and data pipeline orchestration.
* Experience with testing and documentation in DBT.
* Hands-on experience with the AWS cloud platform.
* Ability to write clear, maintainable, and well-documented code.
* Strong problem-solving and communication skills.
Nice-to-Have Qualifications:
* Experience with orchestration tools such as Dagster or similar.
* Familiarity with CI/CD pipelines applied to analytics engineering.
* Knowledge of Python or other scripting languages for data engineering tasks.
* Awareness of data governance and best practices for security.
* Skills in machine learning and ability to identify ML use cases from available data.
* Develop, test, and maintain DBT models and data transformation pipelines.
* Collaborate with data analysts and business stakeholders to understand data requirements.
* Optimize SQL queries and data models for performance and scalability.
* Ensure data quality and implement tests/validations in DBT.
* Maintain documentation for data models, sources, and transformations.
* Participate in code reviews and contribute to best practices in analytics engineering.
2512180202551925024