Data Engineer

As a Data Engineer, your role involves building, maintaining, and optimizing scalable ETL/ELT pipelines for large-scale data processing. You will be responsible for developing and optimizing complex SQL queries, transformations, and warehouse models to ensure efficient data processing. Key Responsibilities: - Create and manage Airflow DAGs for workflow orchestration and scheduling. - Design source-to-target mappings and develop curated data layers for analytics consumption. - Support reporting, dashboarding, and business analytics use cases with reliable datasets. - Work with structured and semi-structured data from multiple internal and external sources. - Monitor pipeline performance, troubleshoot failures, and ensure high data quality standards. - Collaborate cross-functionally with BI, Analytics, Product, and AI/ML teams. - Contribute to the development and enhancement of cloud-based data platforms and architecture. - Maintain technical documentation, metadata, and data lineage processes. Qualifications Required: - Proficiency in building and optimizing ETL/ELT pipelines. - Strong experience in SQL queries, transformations, and warehouse models. - Familiarity with Airflow DAGs and workflow orchestration. - Ability to design source-to-target mappings and develop curated data layers. - Experience working with structured and semi-structured data. - Strong troubleshooting skills and commitment to high data quality standards. - Excellent collaboration skills with cross-functional teams. - Knowledge of cloud-based data platforms and architecture. Please note that the job description also includes collaborating cross-functionally with BI, Analytics, Product, and AI/ML teams, as well as contributing to the development and enhancement of cloud-based data platforms and architecture. As a Data Engineer, your role involves building, maintaining, and optimizing scalable ETL/ELT pipelines for large-scale data processing. You will be responsible for developing and optimizing complex SQL queries, transformations, and warehouse models to ensure efficient data processing. Key Responsibilities: - Create and manage Airflow DAGs for workflow orchestration and scheduling. - Design source-to-target mappings and develop curated data layers for analytics consumption. - Support reporting, dashboarding, and business analytics use cases with reliable datasets. - Work with structured and semi-structured data from multiple internal and external sources. - Monitor pipeline performance, troubleshoot failures, and ensure high data quality standards. - Collaborate cross-functionally with BI, Analytics, Product, and AI/ML teams. - Contribute to the development and enhancement of cloud-based data platforms and architecture. - Maintain technical documentation, metadata, and data lineage processes. Qualifications Required: - Proficiency in building and optimizing ETL/ELT pipelines. - Strong experience in SQL queries, transformations, and warehouse models. - Familiarity with Airflow DAGs and workflow orchestration. - Ability to design source-to-target mappings and develop curated data layers. - Experience working with structured and semi-structured data. - Strong troubleshooting skills and commitment to high data quality standards. - Excellent collaboration skills with cross-functional teams. - Knowledge of cloud-based data platforms and architecture. Please note that the job description also includes collaborating cross-functionally with BI, Analytics, Product, and AI/ML teams, as well as contributing to the development and enhancement of cloud-based data platforms and architecture.