Description

Build and maintain data pipelines and warehousing solutions within an AWS environment.

Responsibilities

• Design and implement ETL processes to move data across cloud environments.
• Manage data warehousing architectures using Snowflake and Amazon Redshift.
• Develop scalable data pipelines using AWS Glue, S3, and Kinesis.
• Apply data modeling techniques to support data science and ML projects.
• Ensure data security and integrity throughout the data lifecycle.

Required Skills

• 6+ years of experience in data engineering roles.
• Expertise with AWS services including AWS Glue, Amazon Redshift, Amazon S3, and Amazon Kinesis.
• Strong programming proficiency in Python, SQL, or Java.
• 2-3 years of hands-on experience with Snowflake and data warehousing concepts.
• Deep understanding of ETL processes and data modeling.
• Solid grasp of cloud computing concepts and data security best practices.
• Experience supporting Data Science and ML project requirements.
• Bachelor's degree or equivalent experience.

Preferred Skills

• Experience with big data technologies such as Apache Spark or Apache Kafka.
• Familiarity with data visualization tools like Tableau or Power BI.
• Understanding of DevOps practices and CI/CD pipelines.

Key Skills

Education

Any Graduate