Description

You will design, build, and maintain high-performance ETL/ELT data pipelines.

Responsibilities

• Design and maintain ETL/ELT pipelines using Python and PySpark.
• Implement complex data manipulation and cleansing with Pandas and NumPy.
• Develop distributed data processing jobs using PySpark for large datasets.
• Automate deployment and orchestration using Docker, Jenkins, Terraform, and CloudFormation.
• Architect cloud-based data ecosystems on AWS (S3, Glue, EMR, Snowflake).

Required Skills

• 5+ years of experience in Data Engineering.
• Expert proficiency in Python, including Pandas and NumPy.
• Hands-on experience with PySpark for scalable data workflows.
• Strong background in DevOps principles and CI/CD tools.
• Experience with AWS data services (S3, Glue, Lambda, Snowflake).
• Advanced SQL knowledge and database performance tuning.
• Familiarity with Apache Spark and Hadoop.

Key Skills

Education

Any Gradute