Data Engineer

We are looking for candidates with strong knowledge on 1. SQL Developer, Snowflake, DBT, ETL, Data Warehouse, Python, and SQL (Primary) - High, 2. SP Optimization, Conduct code reviews, Collaborate with data teams, Follow dbt best practices (Primary) - High • Develop SQL models using dbt Build and maintain modular, reusable data models in dbt Write dbt tests Implement tests to validate data integrity and freshness • Maintain documentation Ensure all models and fields are accurately documented in dbt docs Follow dbt best practices Adhere to naming conventions, folder structure, and model layering standards • Collaborate with data teams Work with analysts and engineers to gather requirements and validate outputs Use version control • Manage changes using Git and follow branching strategies Debug and troubleshoot models Identify and resolve issues in model logic or upstream data • Conduct code reviews Review peer SQL and provide feedback to ensure quality and consistency Optimize SQL for performance Improve query efficiency and manage resource usage Design, build, and maintain data warehouses and data lakes using Snowflake and Azure services. • Develop and maintain ETL pipelines using DBT and Python. • Collaborate with data scientists and analysts to understand their requirements and provide data solutions that meet their needs. • Develop and maintain data quality and governance processes to ensure data accuracy and integrity. • Work with cross-functional teams to design and implement data-driven solutions. • Develop and maintain automated testing and deployment processes for data pipelines. • Stay up-to-date with industry trends and emerging technologies in data engineering. Requirements: Bachelor's degree in Computer Science, Information Technology, or related field. 3+ years of experience in data engineering with expertise in Snowflake, DBT, Data Warehouse, Python, and SQL. • Experience with Azure services, including Azure Data Factory, Azure Databricks, and Azure Storage. Strong understanding of data modeling, data warehousing, and data governance. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills, with the ability to work with cross-functional teams. Experience with Agile development methodologies and version control systems (e.g., Git). • Develop SQL models using dbt Build and maintain modular, reusable data models in dbt Write dbt tests Implement tests to validate data integrity and freshness • Maintain documentation Ensure all models and fields are accurately documented in dbt docs • Follow dbt best practices Adhere to naming conventions, folder structure, and model layering standards Collaborate with data teams • Work with analysts and engineers to gather requirements and validate outputs Use version control • Manage changes using Git and follow branching strategies • Debug and troubleshoot models Identify and resolve issues in model logic or upstream data • Conduct code reviews Review peer SQL and provide feedback to ensure quality and consistency Optimize SQL for performance Improve query efficiency and manage resource usage Design, build, and maintain data warehouses and data lakes using Snowflake and Azure services. • Develop and maintain ETL pipelines using DBT and Python. • Collaborate with data scientists and analysts to understand their requirements and provide data solutions that meet their needs. • Develop and maintain data quality and governance processes to ensure data accuracy and integrity. • Work with cross-functional teams to design and implement data-driven solutions. • Develop and maintain automated testing and deployment processes for data pipelines. • Stay up-to-date with industry trends and emerging technologies in data engineering. • Requirements: Bachelor's degree in Computer Science, Information Technology, or related field. 3+ years of experience in data engineering with expertise in Snowflake, DBT, Data Warehouse, Python, and SQL. • Experience with Azure services, including Azure Data Factory, Azure Databricks, and Azure Storage. • Strong understanding of data modeling, data warehousing, and data governance. • Excellent problem-solving skills and ability to work in a fast-paced environment. • Strong communication and collaboration skills, with the ability to work with cross-functional teams. • Experience with Agile development methodologies and version control systems (e.g., Git).