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About the role
As a Data Engineer, EDM IV at this company, your primary role will involve developing and maintaining data pipelines for ingestion, transformation, and loading of data from various sources using SQL, Python, and DBT. You will be responsible for building and optimizing data models and transformation layers in DBT, working extensively with Snowflake, and supporting AWS-based data architecture. Additionally, you will implement and maintain workflow orchestration using tools like Airflow, enhance existing ETL/ELT workflows, ensure data quality and reliability, collaborate with BI and Analytics teams, troubleshoot data issues, and follow best practices for version control, documentation, and deployment. Key Responsibilities: - Develop and maintain data pipelines using SQL, Python, and DBT - Optimize data models and transformation layers in DBT - Work with Snowflake and AWS-based data architecture - Implement workflow orchestration using Airflow - Enhance existing ETL/ELT workflows for performance and scalability - Ensure data quality, validation, and reliability - Collaborate with BI and Analytics teams - Troubleshoot data issues and support ad-hoc data requests - Follow best practices for version control, documentation, and deployment Minimum Requirements: - 710 years of relevant experience in Data Engineering / Analytics Engineering - Strong expertise in Snowflake, DBT, SQL (advanced), and Python - Experience with AWS services and workflow orchestration tools - Understanding of data warehousing, ETL/ELT, and data modeling concepts - Working knowledge of Power BI - Experience with Git/version control systems Preferred Requirements: - Exposure to data observability / data quality tools - Experience with streaming technologies and data governance tools - Familiarity with data governance and cataloging tools - Experience working in cross-functional or distributed teams If you are interested in this opportunity, please share your resume with shalu.kumari@numerictech.com. As a Data Engineer, EDM IV at this company, your primary role will involve developing and maintaining data pipelines for ingestion, transformation, and loading of data from various sources using SQL, Python, and DBT. You will be responsible for building and optimizing data models and transformation layers in DBT, working extensively with Snowflake, and supporting AWS-based data architecture. Additionally, you will implement and maintain workflow orchestration using tools like Airflow, enhance existing ETL/ELT workflows, ensure data quality and reliability, collaborate with BI and Analytics teams, troubleshoot data issues, and follow best practices for version control, documentation, and deployment. Key Responsibilities: - Develop and maintain data pipelines using SQL, Python, and DBT - Optimize data models and transformation layers in DBT - Work with Snowflake and AWS-based data architecture - Implement workflow orchestration using Airflow - Enhance existing ETL/ELT workflows for performance and scalability - Ensure data quality, validation, and reliability - Collaborate with BI and Analytics teams - Troubleshoot data issues and support ad-hoc data requests - Follow best practices for version control, documentation, and deployment Minimum Requirements: - 710 years of relevant experience in Data Engineering / Analytics Engineering - Strong expertise in Snowflake, DBT, SQL (advanced), and Python - Experience with AWS services and workflow orchestration tools - Understanding of data warehousing, ETL/ELT, and data modeling concepts - Working knowledge of Power BI - Experience with Git/version control systems Preferred Requirements: - Exposure to data observability / data quality tools - Experience with streaming technologies and data governance tools - Familiarity with data governance and cataloging tools - Experience working in cross-functional or distributed teams If you are interested in this opportunity, please share your resume with shalu.kumari@numerictech.com.
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