Data Engineer

Description

Minimum 5 years of hands-on experience in data engineering roles, proven track record of successfully delivering complex data projects.
Advanced proficiency in Python, with a focus on data engineering, familiar with libraries such as Pandas, NumPy, and PySpark
Extensive experience with large-scale data processing and ETL (Extract, Transform, Load) workflows
In-depth knowledge of various database systems (relational and NoSQL), proficiency in writing optimized and efficient SQL queries
Familiarity with Snowflake technologies and its architecture, expertise in data modeling, schema design, and optimization techniques
Practical experience with Apache Spark for large-scale data processing, familiarity with distributed computing principles and practices
Experience with AWS, understanding of cloud architecture and best practices for data engineering
Proficiency with Apache Airflow or similar workflow orchestration tools
Experience in designing, implementing, and maintaining robust data pipelines
Familiarity with data version control systems (e.g., DVC)
Understanding of data governance principles and best practices
Basic understanding of ML algorithms and frameworks
Good to have experience with tools like TensorFlow or PyTorch
Strong problem-solving and analytical thinking abilities.
Bachelor's degree in Computer Science, Data Science, or a related field