Data Engineer

Description

Job Summary: This role involves developing, testing, and maintaining DBT models and data transformation pipelines, collaborating with stakeholders, and ensuring data quality and documentation. Key Highlights: 1. Proficiency in DBT for data modeling and transformation 2. Strong SQL knowledge and experience with cloud platforms such as AWS 3. Development and optimization of DBT models and data pipelines 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. * 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 of data models, sources, and transformations. * Participate in code reviews and contribute to analytics engineering best practices. 2512180202551925024