Data Engineer Python

Proficiency in Python: Strong understanding of Python programming language. Experience with Python libraries and frameworks like Pandas, NumPy, and Django.
Expertise in Apache Airflow: Experience in designing, building, and maintaining data pipelines using Apache Airflow. Knowledge of Airflow’s architecture, including DAGs and Operators.
ETL Processes: Proficiency in data extraction, transformation, and loading processes. Experience with data extraction from various sources, data transformation (cleaning, validating, aggregating, joining, etc.), and loading data into databases or data warehouses.
Database Knowledge: Strong understanding of SQL and NoSQL databases. Proficiency in writing complex queries and applying database optimization techniques.
Data Warehousing: Experience with data warehousing solutions like Amazon Redshift, Google BigQuery, or Microsoft Azure SQL Data Warehouse.
Soft Skills: Strong communication and collaboration skills. Excellent problem-solving skills.
US Citizenship is required to obtain a federal clearance.

Design, develop, and maintain ETL processes using Python and Apache Airflow.
Collaborate with data analysts and other stakeholders to understand and meet their data requirements.
Develop and implement data validation processes to ensure high data quality.
Troubleshoot and resolve issues related to data pipelines.
Optimize data extraction, transformation, and loading (ETL) processes to improve efficiency and performance.
Document and maintain the design and details of data processes and schemas.
Stay updated with the latest industry trends and technologies to ensure data practices remain current.