Data Engineer

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 cloud platforms such as AWS 3. Focus on data quality and query optimization 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 security best practices. * Machine learning skills 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 analytics engineering best practices. 2512180202551925024