Senior Data Engineer/Architect - Snowflake

As a Snowflake Data Engineer, your role will involve designing and implementing scalable data pipelines, integrating diverse data sources, and building a robust data warehouse to support business intelligence and analytics initiatives. Your expertise in DBT, Airbyte, and Airflow, along with strong experience in Kimball dimensional modeling, will be crucial for this role. Key Responsibilities: - Data Integration & Extraction: - Develop and maintain ETL/ELT pipelines using Airbyte and Airflow. - Extract data from multiple sources including APIs, direct database connections, and flat files. - Ensure data quality, consistency, and reliability across all ingestion processes. - Data Modeling & Warehousing: - Design and implement Kimball-style dimensional models in Snowflake. - Build and optimize fact tables and dimension tables to support analytical workloads. - Collaborate with business teams to define and maintain the BUS Matrix for subject areas. - Transformation & Orchestration: - Use DBT to develop modular, testable, and version-controlled transformations. - Implement data quality checks and documentation within DBT workflows. - Collaboration & Governance: - Work closely with business stakeholders to understand requirements and translate them into technical solutions. - Ensure compliance with data governance, security, and privacy standards. Required Skills & Qualifications: - Technical Expertise: - Strong proficiency in Snowflake architecture and performance tuning. - Hands-on experience with DBT, Airbyte, and Airflow. - Solid understanding of Kimball methodology for data warehousing. - Programming & Querying: - Advanced SQL skills and familiarity with Python for ETL scripting. - Experience integrating data from APIs and relational databases. - Soft Skills: - Excellent communication and collaboration skills. - Ability to work in an agile environment and manage multiple priorities. In addition to the above responsibilities and qualifications, any additional details of the company were not provided in the job description. As a Snowflake Data Engineer, your role will involve designing and implementing scalable data pipelines, integrating diverse data sources, and building a robust data warehouse to support business intelligence and analytics initiatives. Your expertise in DBT, Airbyte, and Airflow, along with strong experience in Kimball dimensional modeling, will be crucial for this role. Key Responsibilities: - Data Integration & Extraction: - Develop and maintain ETL/ELT pipelines using Airbyte and Airflow. - Extract data from multiple sources including APIs, direct database connections, and flat files. - Ensure data quality, consistency, and reliability across all ingestion processes. - Data Modeling & Warehousing: - Design and implement Kimball-style dimensional models in Snowflake. - Build and optimize fact tables and dimension tables to support analytical workloads. - Collaborate with business teams to define and maintain the BUS Matrix for subject areas. - Transformation & Orchestration: - Use DBT to develop modular, testable, and version-controlled transformations. - Implement data quality checks and documentation within DBT workflows. - Collaboration & Governance: - Work closely with business stakeholders to understand requirements and translate them into technical solutions. - Ensure compliance with data governance, security, and privacy standards. Required Skills & Qualifications: - Technical Expertise: - Strong proficiency in Snowflake architecture and performance tuning. - Hands-on experience with DBT, Airbyte, and Airflow. - Solid understanding of Kimball methodology for data warehousing. - Programming & Querying: - Advanced SQL skills and familiarity with Python for ETL scripting. - Experience integrating data from APIs and relational databases. - Soft Skills: - Excellent communication and collaboration skills. - Ability to work in an agile environment and manage multiple priorities. In addition to the above responsibilities and qualifications, any additional details of the company were not provided in the job description.