MUST HAVES

• 2+ years of experience writing efficient and scalable Python code, especially for data manipulation and ETL tasks (using libraries like Pandas, PySpark, Dask, etc.);
• Knowledge of Apache Airflow for orchestrating ETL workflows, managing task dependencies, scheduling, and error handling;
• Experience in building, optimizing, and maintaining ETL pipelines for large datasets, focusing on data extraction, transformation, and loading;
• Familiarity with cloud-native storage solutions;
• Understanding and working experience with different file formats;
• Expertise in writing efficient SQL queries for data extraction, transformation, and analysis;
• Familiarity with complex SQL operations (joins, aggregations, window functions, etc.);
• Familiarity with IAM (Identity and Access Management), data encryption, and securing cloud resources and data storage on both Azure, GCP;
• Upper-intermediate English level.

• Design, develop, and maintain ETL pipelines to extract, transform, and load data across various data sources (cloud storage, databases, APIs);
• Use Apache Airflow for orchestrating workflows, scheduling tasks, and managing pipeline dependencies;
• Build and manage data pipelines on Azure and GCP clouds;
• Design and support Data Lake;
• Write Python scripts for data cleansing, transformation, and enrichment using libraries like Pandas, PySpark;
• Analyze logs and metrics from Airflow and cloud services to resolve pipeline failures or inefficiencies.