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About the role
Position Overview We are seeking an experienced Data Engineer with 8+ years of expertise to join our team in Hyderabad. The ideal candidate will bring strong proficiency in cloud data platforms, workflow orchestration, and modern analytics engineering practices. This role demands hands-on experience with Python-based pipeline development, Apache Airflow for orchestration, advanced SQL, dbt for analytics engineering, and cloud data warehouse technologies such as BigQuery. The candidate will be responsible for designing, building, and maintaining robust ETL/ELT data pipelines and data models that support business intelligence and analytics initiatives. Immediate to 15-day notice period joiners are preferred. Key Responsibilities Design, develop, and maintain scalable data pipelines for data processing and transformation Build and manage workflow orchestration using Apache Airflow Develop and maintain data models and transformations using dbt Work with BigQuery or similar cloud data warehouses for data storage and querying Manage and interact with cloud object storage such as GCS or equivalent Implement and optimize ETL/ELT patterns for efficient data ingestion and processing Apply advanced SQL for data querying, transformation, and analysis Collaborate with analytics and engineering teams to support data-driven decision making Ensure data quality, reliability, and performance across data pipelines Apply analytics engineering best practices to deliver clean, well-documented data assets Required Skills Python for data processing and pipeline development Apache Airflow for workflow orchestration Advanced SQL dbt (data build tool) BigQuery or similar cloud data warehouses GCS (Google Cloud Storage) or equivalent cloud object storage ETL/ELT patterns and best practices Data modeling Analytics engineering 8+ years of overall experience in data engineering Preferred (Bonus) Skills Experience with equivalent cloud data warehouse platforms Familiarity with other cloud object storage solutions Immediate to 15-day notice period availability
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